Triple

T11221919
Position Surface form Disambiguated ID Type / Status
Subject Kermanshah Province E265590 entity
Predicate capital P234 FINISHED
Object Kermanshah E210929 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: Kermanshah | Statement: [Kermanshah Province, capital, Kermanshah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kermanshah
Context triple: [Kermanshah Province, capital, Kermanshah]
  • A. Kermanshah chosen
    Kermanshah is a major city in western Iran known for its rich Kurdish culture and proximity to important historical and archaeological sites.
  • B. Khorramabad
    Khorramabad is a city in western Iran and the capital of Lorestan Province, known for its mountainous surroundings and historical sites such as Falak-ol-Aflak Castle.
  • C. Sardasht
    Sardasht is a Kurdish-populated city in Iran’s West Azerbaijan province, historically known for being one of the first civilian targets of large-scale chemical weapons attacks during the Iran–Iraq War.
  • D. Kerman
    Kerman is a major city in southeastern Iran known for its rich history, traditional bazaars, and proximity to desert landscapes.
  • E. Kerman
    Kerman is the surname of Piper Kerman, the American author whose memoir inspired the television series "Orange Is the New Black."
  • 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_69d6aac59460819089b9848b27f57848 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8ec8fb08190b27144ab65f85957 completed April 9, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6af38e3548190a5192894932d9b1d completed May 3, 2026, 2:13 a.m.
Created at: April 8, 2026, 9:30 p.m.