Triple

T4928154
Position Surface form Disambiguated ID Type / Status
Subject Force 136 E110626 entity
Predicate theater P1060 FINISHED
Object Singapore E3670 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: Singapore | Statement: [Force 136, theater, Singapore]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Singapore
Context triple: [Force 136, theater, Singapore]
  • A. Singapore chosen
    Singapore is a sovereign city-state and island nation in Southeast Asia known for its global financial hub status, multicultural society, and highly developed, efficient infrastructure.
  • B. Singapore Bar
    The Singapore Bar is the professional body that regulates and represents qualified advocates and solicitors practicing law in Singapore.
  • C. Nadi–Singapore
    Nadi–Singapore is an international flight route linking Nadi, Fiji with Singapore, serving as a key air corridor between the South Pacific and Southeast Asia.
  • D. Nanyang
    Nanyang is a major prefecture-level city in southwestern Henan Province, China, known for its long history, cultural heritage, and role as a regional economic and transportation hub.
  • E. Malaysia
    Malaysia is a Southeast Asian country on the Malay Peninsula and parts of Borneo, known for its multicultural society, tropical rainforests, and rapidly developing economy.
  • 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_69bd4415190c8190817bee7ec9f9f944 completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7036d8e88190bc4be2975160da23 completed March 20, 2026, 4:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69be77ac88148190a51fa2e9085d6897 completed March 21, 2026, 10:49 a.m.
Created at: March 20, 2026, 1:30 p.m.