Triple

T3592220
Position Surface form Disambiguated ID Type / Status
Subject Shuja Shah Durrani E76050 entity
Predicate exileLocation P10493 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: [Shuja Shah Durrani, exileLocation, Ludhiana]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ludhiana
Context triple: [Shuja Shah Durrani, exileLocation, 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. Jalandhar
    Jalandhar is a major city in the Indian state of Punjab, known as an important commercial and cultural center, particularly famous for its sports goods and manufacturing industries.
  • C. Patiala
    Patiala is a historic city in the Indian state of Punjab, known for its royal heritage, distinctive architecture, and cultural contributions such as the Patiala peg and Patiala salwar.
  • D. 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.
  • E. Hoshiarpur
    Hoshiarpur is a historic city in the Indian state of Punjab, known for its cultural heritage, educational institutions, and agricultural surroundings.
  • 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_69ad85d8042081908af94a04c410dec0 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc15a546481909c72dac80d65e1fb completed March 8, 2026, 6:35 p.m.
NED1 Entity disambiguation (via context triple) batch_69b43305b21081909d7f78dac96ceaa8 completed March 13, 2026, 3:53 p.m.
Created at: March 8, 2026, 3:22 p.m.