Triple

T966813
Position Surface form Disambiguated ID Type / Status
Subject Makar Sankranti E20854 entity
Predicate observedInState P8054 FINISHED
Object Punjab E2323 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: Punjab | Statement: [Makar Sankranti, observedInState, Punjab]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Punjab
Context triple: [Makar Sankranti, observedInState, Punjab]
  • A. Punjab chosen
    Punjab is a historically and culturally rich region of South Asia, known for its fertile agricultural lands, Sikh heritage, and partition between modern-day India and Pakistan.
  • B. Haryana
    Haryana is a northern Indian state known for its significant agricultural output, rapid industrial growth, and proximity to the national capital, New Delhi.
  • C. Sindh
    Sindh is a southeastern province of Pakistan known for its historical Indus Valley heritage, major cities like Karachi and Hyderabad, and a rich Sindhi cultural and linguistic tradition.
  • D. Uttar Pradesh
    Uttar Pradesh is a populous northern Indian state known for its political influence, rich cultural and religious heritage, and historic cities such as Varanasi and Agra.
  • E. Himachal Pradesh
    Himachal Pradesh is a mountainous state in northern India known for its Himalayan landscapes, hill stations, and tourism.
  • 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_69a493b33d2c81909c52c369d3ca8436 completed March 1, 2026, 7:29 p.m.
NER Named-entity recognition batch_69a4b75103688190a14342eef3842984 completed March 1, 2026, 10:01 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac7631d5d081909c1229d1b792ddb6 completed March 7, 2026, 7:02 p.m.
Created at: March 1, 2026, 7:40 p.m.