Triple

T3615849
Position Surface form Disambiguated ID Type / Status
Subject Tarbela Dam E76597 entity
Predicate nearCity P350 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: [Tarbela Dam, nearCity, Haripur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Haripur
Context triple: [Tarbela Dam, nearCity, 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. 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.
  • C. Chakwal
    Chakwal is a city in Pakistan’s Punjab province, known as a regional administrative and commercial center in the Potohar Plateau area.
  • D. Amarkot
    Amarkot is an alternative name for Umarkot, a historic town and district in the Sindh province of Pakistan known for its cultural and Mughal-era significance.
  • E. Jhang
    Jhang is a historic city in the Punjab province of Pakistan, known for its cultural heritage and as the birthplace of several notable figures.
  • 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_69ad85dae2fc81908d1ceadbc6af0089 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc27b5e008190a72a8dab7d736e64 completed March 8, 2026, 6:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3852e60819092db2992e945a4c7 completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:23 p.m.