Triple

T35668059
Position Surface form Disambiguated ID Type / Status
Subject Rajgad Fort E1030627 entity
Predicate hasPart P35 FINISHED
Object Chor Darwaza
Chor Darwaza is a concealed or secondary entrance of Rajgad Fort in Maharashtra, historically used for secret or strategic access.
E2151692 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: Chor Darwaza | Statement: [Rajgad Fort, hasPart, Chor Darwaza]
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: Chor Darwaza
Triple: [Rajgad Fort, hasPart, Chor Darwaza]
Generated description
Chor Darwaza is a concealed or secondary entrance of Rajgad Fort in Maharashtra, historically used for secret or strategic access.

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_69f76e0acfc0819082c8495c2210ce73 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f79fb0522881908ef533985a8dac3e completed May 3, 2026, 7:19 p.m.
NED1 Entity disambiguation (via context triple) batch_6a38728193048190bd9f1fb166ab1be5 completed June 21, 2026, 11:23 p.m.
NEDg Description generation batch_6a3873e563c08190b7f44540f2fe455f completed June 21, 2026, 11:29 p.m.
NED2 Entity disambiguation (via description) batch_6a38744cbac081908be126066e8e79e5 completed June 21, 2026, 11:31 p.m.
Created at: May 3, 2026, 4:05 p.m.