Triple

T4008294
Position Surface form Disambiguated ID Type / Status
Subject Faridabad district E89579 entity
Predicate hasCity P316 FINISHED
Object Faridabad E131142 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: Faridabad | Statement: [Faridabad district, hasCity, Faridabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faridabad
Context triple: [Faridabad district, hasCity, Faridabad]
  • A. Faridabad chosen
    Faridabad is a major industrial city in northern India known for its manufacturing sector and its location within the National Capital Region near New Delhi.
  • B. Ghaziabad
    Ghaziabad is a major industrial and residential city in the Indian state of Uttar Pradesh, forming part of the National Capital Region near Delhi.
  • C. Meerut
    Meerut is a historic city in the Indian state of Uttar Pradesh, known as the place where the Indian Rebellion of 1857 first erupted against British colonial rule.
  • D. Rewari
    Rewari is a historic city in the Indian state of Haryana, located near Delhi and known for its brass industry and strategic position in northern India.
  • E. Gurugram
    Gurugram is a major financial and technology hub in the Indian state of Haryana, known for its modern skyline, multinational corporate offices, and proximity to New Delhi.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa647f80819081180eb267f1cfcc completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589ccd0a48190b98dbe7268df678f completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:34 p.m.