Triple

T19608707
Position Surface form Disambiguated ID Type / Status
Subject Jalandhar–Firozpur railway line E470672 entity
Predicate connectsCity P4245 FINISHED
Object Firozpur 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: Firozpur | Statement: [Jalandhar–Firozpur railway line, connectsCity, Firozpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Firozpur
Context triple: [Jalandhar–Firozpur railway line, connectsCity, Firozpur]
  • A. Hoshiarpur
    Hoshiarpur is a historic city in the Indian state of Punjab, known for its cultural heritage, educational institutions, and agricultural surroundings.
  • B. Ferozepur chosen
    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. Faridkot
    Faridkot is a historic town and district headquarters in the Malwa region of Punjab, India, known for its cultural heritage and agricultural surroundings.
  • D. Gurdaspur
    Gurdaspur is a city in the northern Indian state of Punjab, known for its agricultural surroundings and proximity to the India–Pakistan border.
  • E. Bathinda
    Bathinda is a major city in southwestern Punjab, India, known as an important agricultural, industrial, and military center with historical forts and thermal power plants.
  • 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_69d8e510fa248190b7afb274a1d4cf73 completed April 10, 2026, 11:54 a.m.
NER Named-entity recognition batch_69e640c964fc8190bd1cb60f4b233eaa completed April 20, 2026, 3:05 p.m.
Created at: April 10, 2026, 1:43 p.m.