Triple

T26769878
Position Surface form Disambiguated ID Type / Status
Subject Historic City of Sucre E675048 entity
Predicate contains P35 FINISHED
Object San Lázaro Church
San Lázaro Church is a historic colonial-era Catholic church in Sucre, Bolivia, noted for its religious significance and traditional architecture within the city’s UNESCO-listed historic center.
E1749483 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: San Lázaro Church | Statement: [Historic City of Sucre, contains, San Lázaro Church]
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: San Lázaro Church
Triple: [Historic City of Sucre, contains, San Lázaro Church]
Generated description
San Lázaro Church is a historic colonial-era Catholic church in Sucre, Bolivia, noted for its religious significance and traditional architecture within the city’s UNESCO-listed historic center.

Provenance (5 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69eecda85298819097ee1c38a3d772e7 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6192c45fc819094e7dd70fd9cc333 completed May 2, 2026, 3:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12298053f08190b536019bb3c29880 completed May 23, 2026, 10:26 p.m.
NEDg Description generation batch_6a122a2048408190a3a8cf5a2efa9b08 completed May 23, 2026, 10:28 p.m.
NED2 Entity disambiguation (via description) batch_6a122ac1713481909a80761bb471ef49 completed May 23, 2026, 10:31 p.m.
Created at: April 27, 2026, 4:01 a.m.