Triple

T2838472
Position Surface form Disambiguated ID Type / Status
Subject Malwa (Punjab) E62407 entity
Predicate includesCity P3207 FINISHED
Object Ludhiana E110219 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: Ludhiana | Statement: [Malwa (Punjab), includesCity, Ludhiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ludhiana
Context triple: [Malwa (Punjab), includesCity, Ludhiana]
  • A. Ludhiana chosen
    Ludhiana is a major industrial city in the Indian state of Punjab, known especially for its textile and hosiery manufacturing.
  • B. Ferozepur
    Ferozepur is a historic city in the Indian state of Punjab, known for its strategic location near the India–Pakistan border and its role in various military and independence-era events.
  • C. Chandigarh
    Chandigarh is a planned city in northern India, renowned for its modernist architecture and urban design largely conceived by the Swiss-French architect Le Corbusier.
  • D. Amritsar
    Amritsar is a historic city in the Indian state of Punjab, renowned as the spiritual center of Sikhism and home to the Golden Temple.
  • E. Ambala
    Ambala is a historic city and important military and transportation hub in the northern Indian state of Haryana.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdef015bc81909f6a2ff17b22862f completed March 7, 2026, 8:16 a.m.
NED1 Entity disambiguation (via context triple) batch_69afe8cbaa4081909ff4e9fdf590e352 completed March 10, 2026, 9:47 a.m.
Created at: March 6, 2026, 10:01 p.m.