Triple

T27843689
Position Surface form Disambiguated ID Type / Status
Subject Titabor E703756 entity
Predicate partOfAssemblyConstituency P23217 FINISHED
Object Titabor Assembly constituency
Titabor Assembly constituency is an electoral division in the Assam Legislative Assembly in India, representing the Titabor region and sending a member to the state legislature.
E1791525 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: Titabor Assembly constituency | Statement: [Titabor, partOfAssemblyConstituency, Titabor Assembly constituency]
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: Titabor Assembly constituency
Triple: [Titabor, partOfAssemblyConstituency, Titabor Assembly constituency]
Generated description
Titabor Assembly constituency is an electoral division in the Assam Legislative Assembly in India, representing the Titabor region and sending a member to the state legislature.

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_69ef840d9e3c819093615ebff4ec22be completed April 27, 2026, 3:43 p.m.
NER Named-entity recognition batch_69f638d838c481909fbe470bb85c30b1 completed May 2, 2026, 5:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f7378fd88190a91c125c9998ff0c completed May 24, 2026, 1:03 p.m.
NEDg Description generation batch_6a12f7ba8f048190ac484434da112aeb completed May 24, 2026, 1:06 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbae881c8190a13234bf6ad26f8f completed May 24, 2026, 1:22 p.m.
Created at: April 27, 2026, 6:05 p.m.