Triple

T3772227
Position Surface form Disambiguated ID Type / Status
Subject Western Saudi Arabia E83223 entity
Predicate containsCity P294 FINISHED
Object Taif E87275 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: Taif | Statement: [Western Saudi Arabia, containsCity, Taif]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Taif
Context triple: [Western Saudi Arabia, containsCity, Taif]
  • A. Taif chosen
    Taif is a city in western Saudi Arabia known for its cool climate, rose cultivation, and historical significance as a summer resort and cultural center.
  • B. Taihoku
    Taihoku was the Japanese colonial-era name for Taipei, which served as the administrative and political center of Taiwan under Japanese rule.
  • C. Miyazya
    Miyazya is one of the spring months in the Ethiopian calendar, roughly corresponding to April in the Gregorian calendar.
  • D. Guting
    Guting is a key Taipei Metro station in central Taipei that serves as a transfer point between multiple subway lines.
  • E. Shimaore
    Shimaore is a Bantu language closely related to Comorian, widely spoken by the local population of Mayotte in the Indian Ocean.
  • 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_69ad8b235e608190b5a2b1d1bfcef50b completed March 8, 2026, 2:43 p.m.
NER Named-entity recognition batch_69adcc3219b881908a2f82126f9a679d completed March 8, 2026, 7:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4e52bb2d08190b457dd517ff366d7 completed March 14, 2026, 4:33 a.m.
Created at: March 8, 2026, 3:36 p.m.