Triple

T22425700
Position Surface form Disambiguated ID Type / Status
Subject Old Faridabad E554362 entity
Predicate partOf P40 FINISHED
Object Faridabad NE NERFINISHED

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: [Old Faridabad, partOf, Faridabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Faridabad
Context triple: [Old Faridabad, partOf, 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. Ghaziabad
    Ghaziabad is a village located in the scenic Jhelum Valley region of Azad Jammu and Kashmir, Pakistan.
  • D. 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.
  • E. 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.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e4f2d0c819091aa3558ea2ee630 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15a2d4dd88190a156c24b02b1591b completed April 29, 2026, 1:09 a.m.
Created at: April 16, 2026, 8:47 p.m.