Triple

T16458425
Position Surface form Disambiguated ID Type / Status
Subject Gull Force E399742 entity
Predicate deployedTo P12960 FINISHED
Object Ambon E169607 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: Ambon | Statement: [Gull Force, deployedTo, Ambon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ambon
Context triple: [Gull Force, deployedTo, Ambon]
  • A. Ambon chosen
    Ambon is a major city and port in eastern Indonesia, known as an administrative, economic, and cultural hub in the Maluku region.
  • B. Palu
    Palu is a coastal city on the Indonesian island of Sulawesi, known as the capital of Central Sulawesi province and a regional center for trade and administration.
  • C. Palu
    Palu is a historic town and district in eastern Turkey known for its ancient ruins and location along the Murat River in Elazığ Province.
  • D. Bitung
    Bitung is a port city in North Sulawesi, Indonesia, known as a major gateway for maritime trade and access to the rich marine biodiversity of the Lembeh Strait.
  • E. Ternate
    Ternate is a coastal municipality in the province of Cavite in the Philippines, known for its beaches and historical significance.
  • 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_69d87f2dac988190b74d6e185fa88ba4 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32d7ef5cc819084cfeb1a3e39d3cc completed April 18, 2026, 7:06 a.m.
NED1 Entity disambiguation (via context triple) batch_6a004f51d93081909ede0adcf8e604d4 completed May 10, 2026, 9:26 a.m.
Created at: April 10, 2026, 5:10 a.m.