Triple

T25685500
Position Surface form Disambiguated ID Type / Status
Subject Transport Bhawan, New Delhi E644056 entity
Predicate partOf P40 FINISHED
Object Central Government Offices in New Delhi
Central Government Offices in New Delhi is a major administrative complex in India’s capital that houses key ministries and departments of the Union government.
E40490 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: Central Government Offices in New Delhi | Statement: [Transport Bhawan, New Delhi, partOf, Central Government Offices in New Delhi]
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: Central Government Offices in New Delhi
Triple: [Transport Bhawan, New Delhi, partOf, Central Government Offices in New Delhi]
Generated description
Central Government Offices in New Delhi is a major administrative complex in India’s capital that houses key ministries and departments of the Union government.

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_69e77e8046888190b07ffa58c7e2c37a completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fb7c000c819094efdcbb23ebddae completed May 2, 2026, 1:26 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10c1638fe48190ba1d5f47caed6c30 completed May 22, 2026, 8:49 p.m.
NEDg Description generation batch_6a10c2a7e0b48190b17dd8b9bd8ccc0f completed May 22, 2026, 8:55 p.m.
NED2 Entity disambiguation (via description) batch_6a10c332191c81908f970d18fb2f37e9 completed May 22, 2026, 8:57 p.m.
Created at: April 21, 2026, 8:07 p.m.