Triple

T5075764
Position Surface form Disambiguated ID Type / Status
Subject Khandwa E114390 entity
Predicate region P40 FINISHED
Object Nimar E125271 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: Nimar | Statement: [Khandwa, region, Nimar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nimar
Context triple: [Khandwa, region, Nimar]
  • A. Nimar chosen
    Nimar is a culturally distinct region in southwestern Madhya Pradesh, India, known for its tribal communities, cotton production, and location along the Narmada River.
  • B. Carrù
    Carrù is a small town in Italy’s Piedmont region, known as the birthplace of former Italian President Luigi Einaudi and for its wine and truffle traditions.
  • C. Senigallia
    Senigallia is a historic coastal town in Italy’s Marche region, known for its Adriatic seaside resort, Renaissance heritage, and well-preserved old town.
  • D. Rissani
    Rissani is a historic town in eastern Morocco, known as a gateway to the Sahara Desert and an important former caravan and trading center.
  • E. Nimarata
    Nimarata is the birth name of American politician Nikki Haley, who served as U.S. ambassador to the United Nations and governor of South Carolina.
  • 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_69bd443dbf908190a9401e9c2dc7bd7d completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd74d2243481908c1ae62f7123c4e9 completed March 20, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69beb121fa388190ab3909d20f014b6f completed March 21, 2026, 2:54 p.m.
Created at: March 20, 2026, 1:39 p.m.