Triple

T5168636
Position Surface form Disambiguated ID Type / Status
Subject Bandar Shahpur E116619 entity
Predicate hasAlternateName P39 FINISHED
Object Bandar Shahpoor E116619 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: Bandar Shahpoor | Statement: [Bandar Shahpur, hasAlternateName, Bandar Shahpoor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandar Shahpoor
Context triple: [Bandar Shahpur, hasAlternateName, Bandar Shahpoor]
  • A. Bandar Shahpur chosen
    Bandar Shahpur is a port city in southwestern Iran on the Persian Gulf that historically served as a key maritime and logistical hub, including during World War II supply routes.
  • B. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • 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. Sadabad
    Sadabad is a town located in India’s culturally significant Braj region, traditionally associated with the life of Lord Krishna.
  • E. Asadabad
    Asadabad is a small but strategically important city in eastern Afghanistan, serving as the capital of Kunar Province near the Pakistani border.
  • 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_69bd445ff97c81909a2615cc56235470 completed March 20, 2026, 12:58 p.m.
NER Named-entity recognition batch_69bd794dd9988190922e138f2a9a3c62 completed March 20, 2026, 4:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69bee077effc8190bdd5771db64d1578 completed March 21, 2026, 6:16 p.m.
Created at: March 20, 2026, 1:45 p.m.