Triple

T18982075
Position Surface form Disambiguated ID Type / Status
Subject Morvi E464452 entity
Predicate locatedIn P40 FINISHED
Object Morbi district 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: Morbi district | Statement: [Morvi, locatedIn, Morbi district]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Morbi district
Context triple: [Morvi, locatedIn, Morbi district]
  • A. Morbi district chosen
    Morbi district is an administrative district in the state of Gujarat, India, known for its ceramic industry and the town of Morbi.
  • B. Vikarabad district
    Vikarabad district is an administrative region in the Indian state of Telangana, known for its hilly terrain, forests, and role as a watershed area for rivers in the region.
  • C. Sheema District
    Sheema District is an administrative district in southwestern Uganda known for its predominantly rural communities and agricultural-based economy.
  • D. Marjeyoun District
    Marjeyoun District is an administrative district in southern Lebanon known for its strategic location near the borders with Israel and Syria and its mix of agricultural villages and historic towns.
  • E. Buyende District
    Buyende District is an administrative district in eastern Uganda, known for its rural communities and location along the shores of Lake Kyoga.
  • 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_69d8dd008af48190a97ff1c6488edf1b completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5d65d27548190b86d4c5f5b51d809 completed April 20, 2026, 7:31 a.m.
Created at: April 10, 2026, 12:01 p.m.