Triple

T2930531
Position Surface form Disambiguated ID Type / Status
Subject Noida E78949 entity
Predicate hasMetroConnectivityWith P3791 FINISHED
Object Ghaziabad E79192 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: Ghaziabad | Statement: [Noida, hasMetroConnectivityWith, Ghaziabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ghaziabad
Context triple: [Noida, hasMetroConnectivityWith, Ghaziabad]
  • A. Ghaziabad chosen
    Ghaziabad is a major industrial and residential city in the Indian state of Uttar Pradesh, forming part of the National Capital Region near Delhi.
  • B. 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.
  • C. Faridabad
    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.
  • D. Bareilly
    Bareilly is a historic city in the Indian state of Uttar Pradesh, known as a major center of the 1857 uprising against British colonial rule and now an important commercial and cultural hub.
  • E. Moradabad
    Moradabad is a major city in northern India known for its brass handicraft industry and is located in the state of Uttar Pradesh.
  • 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_69ad8b0d40b481908bc2a5fa2e73c3fb completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69ad9e0fec048190bdd70c60ec5c92cd completed March 8, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1de8f4d94819086527165d7da11c5 completed March 11, 2026, 9:28 p.m.
Created at: March 8, 2026, 2:55 p.m.