Triple

T3294623
Position Surface form Disambiguated ID Type / Status
Subject Gomti E69183 entity
Predicate majorCityOnBanks P14915 FINISHED
Object Jaunpur E352178 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: Jaunpur | Statement: [Gomti, majorCityOnBanks, Jaunpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jaunpur
Context triple: [Gomti, majorCityOnBanks, Jaunpur]
  • A. Jaunpur chosen
    Jaunpur is a historic city in the Indian state of Uttar Pradesh, known for its medieval architecture and cultural heritage.
  • B. Shahjahanpur
    Shahjahanpur is a prominent city in the Rohilkhand region of Uttar Pradesh, India, known for its historical significance and regional commercial importance.
  • C. Ghazipur
    Ghazipur is a city in the Indian state of Uttar Pradesh, known for its historical significance and as a regional hub in eastern Uttar Pradesh.
  • D. Farrukhabad
    Farrukhabad is a city and parliamentary constituency in the Indian state of Uttar Pradesh, known historically for its trade and cultural significance.
  • E. Hajipur
    Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
  • 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_69ad859d45748190b0742408c954b39f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb07661748190bf57469e101c5283 completed March 8, 2026, 5:23 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bb385f48190a67051e8681fa64d completed March 12, 2026, 11:26 p.m.
Created at: March 8, 2026, 3:10 p.m.