Triple

T11135423
Position Surface form Disambiguated ID Type / Status
Subject Fars Province E263396 entity
Predicate containsCity P294 FINISHED
Object Firuzabad E587455 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: Firuzabad | Statement: [Fars Province, containsCity, Firuzabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Firuzabad
Context triple: [Fars Province, containsCity, Firuzabad]
  • A. Firuzabad chosen
    Firuzabad is a historic city in Iran renowned for its Sassanian-era archaeological sites and distinctive circular urban plan.
  • B. Nurabad
    Nurabad is a city in western Iran that serves as a local urban center within Lorestan Province.
  • C. Piranshahr
    Piranshahr is a predominantly Kurdish city in northwestern Iran known for its mountainous surroundings and role as a regional commercial center.
  • D. Azarshahr
    Azarshahr is a city in northwestern Iran known for its location within East Azerbaijan Province and its role as a local administrative and economic center.
  • E. Nahavand
    Nahavand is a historic city in western Iran known as the site of a decisive 7th-century battle that contributed to the fall of the Sasanian Empire.
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e85daddc8190a1ae2a4a75cc8d50 completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69f69b76e0cc8190aa7303347e0183d4 completed May 3, 2026, 12:48 a.m.
Created at: April 8, 2026, 9:28 p.m.