Triple

T12606661
Position Surface form Disambiguated ID Type / Status
Subject Topi E300995 entity
Predicate hasNearbySettlement P4647 FINISHED
Object Haripur E53477 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: Haripur | Statement: [Topi, hasNearbySettlement, Haripur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haripur
Context triple: [Topi, hasNearbySettlement, Haripur]
  • A. Haripur chosen
    Haripur is a city in northern Pakistan known as an administrative and commercial center in the Hazara region of Khyber Pakhtunkhwa.
  • B. Bahawalnagar
    Bahawalnagar is a prominent city in Pakistan’s Punjab province, known as an agricultural and commercial hub near the border with India.
  • C. Attock
    Attock is a historic city in northern Pakistan strategically located along the Indus River, long serving as a key gateway between the Punjab region and Khyber Pakhtunkhwa.
  • D. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
  • E. Khanewal
    Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
  • 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_69d7bdea2ca881908f379526c13b1145 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d954e7f2dc8190a42cab7a0e5ea7f3 completed April 10, 2026, 7:52 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6719488748190a07bc7335d62b8e8 completed May 2, 2026, 9:50 p.m.
Created at: April 9, 2026, 5:11 p.m.