Triple

T7333590
Position Surface form Disambiguated ID Type / Status
Subject Hormozgan Province E169066 entity
Predicate hasCity P316 FINISHED
Object Bandar Lengeh E657497 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 Lengeh | Statement: [Hormozgan Province, hasCity, Bandar Lengeh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandar Lengeh
Context triple: [Hormozgan Province, hasCity, Bandar Lengeh]
  • A. Bandar Lengeh chosen
    Bandar Lengeh is a coastal city and important maritime port on the Persian Gulf in southern Iran’s Hormozgan Province.
  • B. Pelabuhan Ratu
    Pelabuhan Ratu is a coastal town and bay in West Java, Indonesia, known for its scenic beaches, strong surf, and local fishing culture.
  • C. Padang Bai
    Padang Bai is a small coastal village and port in eastern Bali, Indonesia, known as a gateway to the nearby islands and for its beaches and dive sites.
  • D. Pasir Gudang
    Pasir Gudang is an industrial port city in the state of Johor, Malaysia, known for its heavy industries and maritime activities along the Straits of Johor.
  • E. Pasir Mas
    Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
  • 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_69c68a568a6481908f11e20db7bc8446 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f0c0f87081908d12ac14d4591e23 completed March 27, 2026, 9:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7fa82498c8190b1898a8c27cec71d completed March 28, 2026, 3:57 p.m.
Created at: March 27, 2026, 3:04 p.m.