Triple

T25320817
Position Surface form Disambiguated ID Type / Status
Subject Pangrango regional train E634875 entity
Predicate operatesIn P82 FINISHED
Object Bogor metropolitan area
The Bogor metropolitan area is a densely populated urban region in West Java, Indonesia, centered on the city of Bogor and integrated into the greater Jakarta metropolitan corridor.
E29215 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: Bogor metropolitan area | Statement: [Pangrango regional train, operatesIn, Bogor metropolitan area]
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: Bogor metropolitan area
Triple: [Pangrango regional train, operatesIn, Bogor metropolitan area]
Generated description
The Bogor metropolitan area is a densely populated urban region in West Java, Indonesia, centered on the city of Bogor and integrated into the greater Jakarta metropolitan corridor.

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_69e75a9847c08190bb02990d06d5ffb7 completed April 21, 2026, 11:08 a.m.
NER Named-entity recognition batch_69f4968e4e70819096256546d76f6e6b completed May 1, 2026, 12:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11c7e002708190a33c46e042f7f5c5 completed May 23, 2026, 3:29 p.m.
NEDg Description generation batch_6a11c8bf3ee08190964adc437235340b completed May 23, 2026, 3:33 p.m.
NED2 Entity disambiguation (via description) batch_6a11c981c70c8190bfe0da42958fa494 completed May 23, 2026, 3:36 p.m.
Created at: April 21, 2026, 1:28 p.m.