Triple

T7856504
Position Surface form Disambiguated ID Type / Status
Subject Rawalpindi Railway Station E182388 entity
Predicate connectsTo P845 FINISHED
Object Sialkot E101948 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: Sialkot | Statement: [Rawalpindi Railway Station, connectsTo, Sialkot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sialkot
Context triple: [Rawalpindi Railway Station, connectsTo, Sialkot]
  • A. Sialkot chosen
    Sialkot is a major industrial city in Pakistan’s Punjab province, renowned globally for its production of sports goods and surgical instruments.
  • B. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
  • C. Khanewal
    Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
  • D. Bahawalpur
    Bahawalpur is a historic city in southern Punjab, Pakistan, known for its former princely state status, grand palaces, and proximity to the Cholistan Desert.
  • E. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • 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_69ca82887fd48190975896bf38c4596b completed March 30, 2026, 2:02 p.m.
NER Named-entity recognition batch_69cb1a75de548190af5653409a3b3881 completed March 31, 2026, 12:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69ccec5f00b48190b35f7cab67e7e5f9 completed April 1, 2026, 9:58 a.m.
Created at: March 30, 2026, 4:52 p.m.