Triple

T25677945
Position Surface form Disambiguated ID Type / Status
Subject Kolkata Municipal Corporation E643857 entity
Predicate leaderTitle P8 FINISHED
Object Deputy Mayor of Kolkata
The Deputy Mayor of Kolkata is a senior elected official of the Kolkata Municipal Corporation who assists the Mayor in overseeing the city’s municipal governance and administration.
E1693889 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: Deputy Mayor of Kolkata | Statement: [Kolkata Municipal Corporation, leaderTitle, Deputy Mayor of Kolkata]
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: Deputy Mayor of Kolkata
Triple: [Kolkata Municipal Corporation, leaderTitle, Deputy Mayor of Kolkata]
Generated description
The Deputy Mayor of Kolkata is a senior elected official of the Kolkata Municipal Corporation who assists the Mayor in overseeing the city’s municipal governance and administration.

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_69e77e7f69808190ad27df1006f6037a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb7700888190a773a390033bf320 completed May 2, 2026, 1:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cbeff55c819086d40aa9eabc4bb3 completed May 22, 2026, 9:34 p.m.
NEDg Description generation batch_6a10cde4cc7c819082eea238a1e4a786 completed May 22, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a10ce8ce9dc819097e693a12731bf5d completed May 22, 2026, 9:45 p.m.
Created at: April 21, 2026, 7:42 p.m.