Triple

T3670686
Position Surface form Disambiguated ID Type / Status
Subject Multani E77870 entity
Predicate namedAfter P63 FINISHED
Object 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: Multan | Statement: [Multani, namedAfter, Multan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Multan
Context triple: [Multani, namedAfter, 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. Sukkur
    Sukkur is a major city in Pakistan known for its strategic location on the Indus River and its role as an important commercial and cultural center in northern Sindh.
  • 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. 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. Khairpur
    Khairpur is a historic city in Sindh, Pakistan, known for its former princely state status under the Talpur rulers and its rich cultural and architectural heritage.
  • 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_69b5b7446bf88190848eb7ecb0e067bd completed March 14, 2026, 7:30 p.m.
Created at: March 8, 2026, 3:25 p.m.