Triple

T25445537
Position Surface form Disambiguated ID Type / Status
Subject Uluberia Lok Sabha constituency E637625 entity
Predicate hasAssemblySegment P121483 FINISHED
Object Uluberia Purba
Uluberia Purba is a legislative assembly constituency in West Bengal, India, that forms part of the Uluberia Lok Sabha parliamentary seat.
E1678684 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: Uluberia Purba | Statement: [Uluberia Lok Sabha constituency, hasAssemblySegment, Uluberia Purba]
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: Uluberia Purba
Triple: [Uluberia Lok Sabha constituency, hasAssemblySegment, Uluberia Purba]
Generated description
Uluberia Purba is a legislative assembly constituency in West Bengal, India, that forms part of the Uluberia Lok Sabha parliamentary seat.

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_69e75db7c5048190b8da9cd7eeedb610 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f70346cc8190b7ed6b5a86a508cd completed May 2, 2026, 1:07 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11272052548190a5a2abdde29be1ee completed May 23, 2026, 4:03 a.m.
NEDg Description generation batch_6a1134f024f88190a9d38f99d71fa849 completed May 23, 2026, 5:02 a.m.
NED2 Entity disambiguation (via description) batch_6a113610d1d8819097ce5070e47a7645 completed May 23, 2026, 5:07 a.m.
Created at: April 21, 2026, 2:01 p.m.