Triple

T2596465
Position Surface form Disambiguated ID Type / Status
Subject Syrah E58242 entity
Predicate synonym P3575 FINISHED
Object Shiraz E38586 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: Shiraz | Statement: [Syrah, synonym, Shiraz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shiraz
Context triple: [Syrah, synonym, Shiraz]
  • A. Shiraz chosen
    Shiraz is a dark-skinned wine grape variety, also known as Syrah, widely used to produce full-bodied red wines around the world.
  • B. Shiraz, Iran
    Shiraz, Iran is a historic city in southwestern Iran renowned for its rich Persian cultural heritage, poetry, gardens, and wine-making tradition.
  • C. Kerman
    Kerman is a small city in California’s San Joaquin Valley, known for its agricultural economy and location west of Fresno.
  • D. Kerman
    Kerman is a major city in southeastern Iran known for its rich history, traditional bazaars, and proximity to desert landscapes.
  • E. Hamadan
    Hamadan is an ancient city in western Iran, historically significant as a major center of Persian Jewish life and one of the oldest continuously inhabited cities in the region.
  • 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_69ab4ac14040819098b13f4a27d5c8ff completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd42b3cd4819093b2cab78de1f66c completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af83c798088190944e7d754aa9aa06 completed March 10, 2026, 2:36 a.m.
Created at: March 6, 2026, 9:49 p.m.