ykolo/entityconcepts-smoke

platovec — Wikipedia entities, documents, linearity triples & ZELDA links

A dataset for studying entity representations in LLMs: how entities are encoded, how those representations form, and their causal effects.

Built from a seed entity list (the factual relations of Hernandez et al. 2024, by title, plus ZELDA mention targets, by Wikipedia page id) by joining wikimedia/structured-wikipedia (text + links) and the Wikidata API (labels / aliases / properties).

Configs

config	granularity	description
entities	one row / entity	the entity, its text, abstract, aliases, properties, links
documents	one row / document	mention positions of entities within a document
triples	one row / linearity fact	(subject, object) + chosen template + QIDs + Wikidata property
templates	one row / relation	candidate prompt templates per relation (best-first)
links	one row / ZELDA document	entity-linking mentions for retrieval eval (split test)

from datasets import load_dataset
entities  = load_dataset("ykolo/entityconcepts", "entities",  split="train")
documents = load_dataset("ykolo/entityconcepts", "documents", split="train")
triples   = load_dataset("ykolo/entityconcepts", "triples",   split="train")
links     = load_dataset("ykolo/entityconcepts", "links",     split="test")

entities

column	type	description
qid	str	Wikidata QID (row key)
label	str	entity name (Wikipedia article title)
description	str	one-line description
alias	list[str]	alternative names (Wikidata "also known as", English)
wikidata_url	str
wikipedia_url	str
what_links_here	list[str]	QIDs of seed entities whose article links to this one
properties	list[{property_id, value}]	Wikidata claims (value = QID for items, rendered text otherwise)
text	str	flat article text (reconstructed from structured-wikipedia sections)
abstract	str | null	article lead/abstract (from structured-wikipedia)
page_id	int | null	English Wikipedia page id (structured-wikipedia identifier)
n_characters	int | null	article length (structured-wikipedia version.number_of_characters)
origin	list[str]	seed origin(s): linearity and/or zelda
n_mentions	int	total mention occurrences across the documents table

documents

One row = one document (an entity's Wikipedia article). Lists are aligned by position: entity_ids[i] ↔ aliases[i] ↔ index[i]. The document text is entities[document_id].text (not duplicated here). Use it to extract an entity's activations at its mention positions across several documents (self-mention ⇔ document_id ∈ entity_ids).

column	type	description
document_id	str	QID of the entity whose article is this document (→ entities.qid)
entity_ids	list[str]	QID of each mentioned entity (repeats for multiple mentions)
aliases	list[str]	surface form found in the text for each mention
index	list[[int, int]]	character [start, end] offsets in the document's text
entity_count	int	number of distinct entities mentioned in the document

triples

Facts from the factual linearity relations (one row per (subject, object) sample).

column	type	description
id	int
relation_id	str | null	mapped Wikidata property, e.g. P36 (null if unmapped)
relation_name	str	human-readable name, e.g. "country capital city"
template	str	prompt template with {} as the subject placeholder
template_id	int | null	index of the template used in templates.templates[] (best-first ⇒ 0)
subject	str	subject
subject_qid	str|null	qid of subject
object	str	object
object_qid	str|null	qid of object

links

Entity-linking documents from the ZELDA dataset, for retrieval evaluation. One row = one document; each mention's ZELDA wikipedia_id is matched to the page_id column of entities to recover its QID. Split test (the source column gives the ZELDA subset, e.g. aida-b; train is available too if built). Lists aligned by position: entity_ids[i] ↔ index[i] ↔ wikipedia_ids[i] ↔ wikipedia_titles[i].

column	type	description
source	str	split origin (train, or test set name e.g. aida-b)
document_id	str | null	QID of the document's own Wikipedia page (train only; via entities.page_id)
entity_ids	list[str]	QID of each mention's gold entity
index	list[[int, int]]	character [start, end] offsets in text
text	str	document text
wikipedia_ids	list[int]	raw ZELDA Wikipedia page ids of the mentions (traceability)
wikipedia_titles	list[str]	ZELDA Wikipedia titles of the mentions (traceability)

Mentions whose wikipedia_id is not present in entities (entity not scraped) are dropped (logged).

Construction

• seed entities: subjects + objects of the factual relations (by title) + ZELDA mention targets (by page_id). origin records which source(s) each entity came from.
• entities / documents: text + link graph from hugging face wikimedia/structured-wikipedia (enwiki); aliases & properties from the Wikidata API; abstract/text from structured-wikipedia; disambiguation pages filtered out;
• triples: linearity relations; relation_id is the Wikidata P-id from a static mapping; template is the best prompt per relation (max partial-match in generation).
• links: ZELDA entity-linking documents; mention wikipedia_id matched to entities.page_id → QID.

Code: https://github.com/siemovit/platovec