Triple

T19118645
Position Surface form Disambiguated ID Type / Status
Subject Saurashtra–Kutch E467976 entity
Predicate hasCulturalSite P1098 FINISHED
Object Lakhpat 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: Lakhpat | Statement: [Saurashtra–Kutch, hasCulturalSite, Lakhpat]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lakhpat
Context triple: [Saurashtra–Kutch, hasCulturalSite, Lakhpat]
  • A. Lakhpat chosen
    Lakhpat is a historic fortified town in the Kutch district of Gujarat, India, known for its massive walls and once-thriving port on the Arabian Sea.
  • B. Umarkhed
    Umarkhed is a town in the Yavatmal district of Maharashtra, India, known as a local commercial and administrative center for the surrounding rural region.
  • C. Nakodar
    Nakodar is a prominent town in the Indian state of Punjab, known for its historical significance and cultural heritage within the Jalandhar region.
  • D. Randhawa
    Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
  • E. Nagaur
    Nagaur is a historic city in Rajasthan, India, known for its medieval fort, cultural heritage, and role as an important center in the Marwar region.
  • 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_69d8dd06a26481908039e2a1bae8c597 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e3c756a88190942930e6ae7242a7 completed April 20, 2026, 8:28 a.m.
Created at: April 10, 2026, 12:05 p.m.