Triple

T35385041
Position Surface form Disambiguated ID Type / Status
Subject Kanpur Dehat E1022765 entity
Predicate containsTown P847 FINISHED
Object Pukhrayan
Pukhrayan is a town in the Kanpur Dehat district of Uttar Pradesh, India, known for its religious significance and local trade.
E2157081 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: Pukhrayan | Statement: [Kanpur Dehat, containsTown, Pukhrayan]
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: Pukhrayan
Triple: [Kanpur Dehat, containsTown, Pukhrayan]
Generated description
Pukhrayan is a town in the Kanpur Dehat district of Uttar Pradesh, India, known for its religious significance and local trade.

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_69f76df28d8c819089f2c5799fe7d079 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f794f50080819095ff3c2cefc74fea completed May 3, 2026, 6:33 p.m.
NED1 Entity disambiguation (via context triple) batch_6a389148394c81908c1311720864dafd completed June 22, 2026, 1:35 a.m.
NEDg Description generation batch_6a389218b7248190aab0663e9b0f3381 completed June 22, 2026, 1:38 a.m.
NED2 Entity disambiguation (via description) batch_6a3894ca2a788190a7816a8be18c3462 completed June 22, 2026, 1:50 a.m.
Created at: May 3, 2026, 4:03 p.m.