Triple

T3670701
Position Surface form Disambiguated ID Type / Status
Subject Multani E77870 entity
Predicate geographicCenter P1822 FINISHED
Object city of Multan E90805 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: city of Multan | Statement: [Multani, geographicCenter, city of Multan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Multan
Context triple: [Multani, geographicCenter, city of Multan]
  • A. Multan chosen
    Multan is a historic city in southern Punjab, Pakistan, renowned as a major cultural, commercial, and Sufi spiritual center with a legacy spanning over two millennia.
  • B. Lahore
    Lahore is a major cultural, historical, and economic center of Pakistan, known for its rich Mughal heritage, educational institutions, and role in the region’s political history.
  • C. 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.
  • D. Gujranwala
    Gujranwala is a major industrial city in Pakistan’s Punjab province, known for its manufacturing base and historical significance in the region.
  • E. Peshawar
    Peshawar is one of Pakistan’s oldest and largest cities, a historic cultural and economic hub located near the Khyber Pass in the country’s northwest.
  • 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_69ad85e083008190b2e1b7085fe500bd completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc42c96648190abbd5d23b25d6a6b completed March 8, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b48850515c8190bdb9ddcfc0a13f4e completed March 13, 2026, 9:57 p.m.
Created at: March 8, 2026, 3:25 p.m.