Triple

T4512990
Position Surface form Disambiguated ID Type / Status
Subject Navadvipa E102092 entity
Predicate locatedInDistrict P40 FINISHED
Object Nadia district E164529 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: Nadia district | Statement: [Navadvipa, locatedInDistrict, Nadia district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nadia district
Context triple: [Navadvipa, locatedInDistrict, Nadia district]
  • A. Nadia district chosen
    Nadia district is an administrative district in the Indian state of West Bengal, known for its historical towns, cultural heritage, and agricultural economy.
  • B. Badrashin district
    Badrashin district is an administrative region in Giza Governorate, Egypt, known for encompassing several important archaeological and historical sites near ancient Memphis.
  • C. Rusafa District
    Rusafa District is a central administrative area of Baghdad, Iraq, known for encompassing key cultural and historical landmarks, including major monuments and public institutions.
  • D. Shabran District
    Shabran District is an administrative region in northeastern Azerbaijan known for its historical sites and location near the Caspian Sea.
  • E. Qibla district
    Qibla district is a central urban area in Kuwait City known for its commercial activity, historic mosques, and proximity to key government and financial institutions.
  • 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_69bd43d6251c81909deecce3e6e9d69c completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5722d8fc81909c5f2d9a38d17a6b completed March 20, 2026, 2:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd7f8b19ac819099e9249d31660f52 completed March 20, 2026, 5:10 p.m.
Created at: March 20, 2026, 1:02 p.m.