Triple

T15648350
Position Surface form Disambiguated ID Type / Status
Subject Kutchi E376238 entity
Predicate hasDialect P4251 FINISHED
Object Anjar Kutchi E372444 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: Anjar Kutchi | Statement: [Kutchi, hasDialect, Anjar Kutchi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Anjar Kutchi
Context triple: [Kutchi, hasDialect, Anjar Kutchi]
  • A. Anjar
    Anjar is a historic town in Lebanon renowned for its well-preserved Umayyad-era archaeological site and distinctive urban layout.
  • B. Anjar chosen
    Anjar is a historic town in the Kutch district of Gujarat, India, known for its traditional architecture and its devastation in the 2001 Gujarat earthquake.
  • C. Arjan Garh
    Arjan Garh is an elevated station on the Delhi Metro network serving the southern outskirts of Delhi near the Haryana border.
  • D. Ranakpur
    Ranakpur is a village in Rajasthan, India, renowned for its intricately carved Jain temples and stunning marble architecture set amid the Aravalli hills.
  • E. Sujangarh
    Sujangarh is a town in the Indian state of Rajasthan known for its local markets, temples, and role as a regional commercial center.
  • 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_69d85cd1564c8190991adda63bfab4b0 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04ed7212c8190be6ff76afa25f7ca completed April 16, 2026, 2:52 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff67936e388190913c9060194e5b53 completed May 9, 2026, 4:57 p.m.
Created at: April 10, 2026, 4:15 a.m.