Triple

T27254231
Position Surface form Disambiguated ID Type / Status
Subject Ajodhya Hills E687567 entity
Predicate nearestRailwayStation P4625 FINISHED
Object Barabhum
Barabhum is a railway station in West Bengal, India, that serves as the primary rail access point for the Ajodhya Hills region.
E1763706 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: Barabhum | Statement: [Ajodhya Hills, nearestRailwayStation, Barabhum]
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: Barabhum
Triple: [Ajodhya Hills, nearestRailwayStation, Barabhum]
Generated description
Barabhum is a railway station in West Bengal, India, that serves as the primary rail access point for the Ajodhya Hills region.

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_69ef35567e808190a94458cd44ebff0c completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f626b8bb708190bac3a4be92279165 completed May 2, 2026, 4:30 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1262812ee481908344110c4d018a37 completed May 24, 2026, 2:29 a.m.
NEDg Description generation batch_6a126390f0d88190b2355174dfe50a85 completed May 24, 2026, 2:33 a.m.
NED2 Entity disambiguation (via description) batch_6a12641d09a881908d4fd0d679ff38b3 completed May 24, 2026, 2:36 a.m.
Created at: April 27, 2026, 10:47 a.m.