Triple

T17294212
Position Surface form Disambiguated ID Type / Status
Subject Shush E419862 entity
Predicate locatedNear P294 FINISHED
Object Ahvaz NE NERFINISHED

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: Ahvaz | Statement: [Shush, locatedNear, Ahvaz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ahvaz
Context triple: [Shush, locatedNear, Ahvaz]
  • A. Ahvaz chosen
    Ahvaz is a major industrial city in southwestern Iran and the capital of Khuzestan Province, known for its oil industry and location along the Karun River.
  • B. 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.
  • C. Sanandaj
    Sanandaj is the capital of Iran’s Kurdistan Province, known for its Kurdish culture, traditional music, and mountainous surroundings in western Iran.
  • D. Shahrekord
    Shahrekord is a city in western Iran known as the capital of Chaharmahal and Bakhtiari Province and for its high elevation and cool climate.
  • E. Zahedan
    Zahedan is a major city in southeastern Iran and the capital of Sistan and Baluchestan Province, near the borders with Pakistan and Afghanistan.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d886db32608190a61e18862c5a8af6 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e437869ec08190b4a63fb1ee6a71ee completed April 19, 2026, 2:01 a.m.
Created at: April 10, 2026, 5:40 a.m.