Triple

T11509968
Position Surface form Disambiguated ID Type / Status
Subject Derajat E272882 entity
Predicate namedAfter P63 FINISHED
Object Dera Ghazi Khan E227624 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: Dera Ghazi Khan | Statement: [Derajat, namedAfter, Dera Ghazi Khan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dera Ghazi Khan
Context triple: [Derajat, namedAfter, Dera Ghazi Khan]
  • A. Dera Ghazi Khan chosen
    Dera Ghazi Khan is a major city in southern Punjab, Pakistan, known as an important cultural and economic center of the Seraiki-speaking region.
  • B. Vehari
    Vehari is a city in the Punjab province of Pakistan, known as an agricultural and educational hub in the region.
  • C. Khanewal
    Khanewal is a prominent city in Pakistan’s Punjab province, known as an important railway junction and agricultural trade center.
  • D. Rahim Yar Khan
    Rahim Yar Khan is a major city in southern Punjab, Pakistan, known as an important commercial and agricultural center in the Seraiki-speaking region.
  • E. Shikarpur
    Shikarpur is a historic city in the Sindh province of Pakistan, known for its old trading heritage and distinctive cultural and architectural traditions.
  • 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_69d6aae2c3748190bed2ea50dfb160dc completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d86db65eb081908613a1002c6a4fb4 completed April 10, 2026, 3:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69e625055dfc81909a87418a3ed40027 completed April 20, 2026, 1:07 p.m.
Created at: April 8, 2026, 9:36 p.m.