Triple

T16984665
Position Surface form Disambiguated ID Type / Status
Subject Osakasayama E412031 entity
Predicate locatedNear P294 FINISHED
Object Sakai E8407 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: Sakai | Statement: [Osakasayama, locatedNear, Sakai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sakai
Context triple: [Osakasayama, locatedNear, Sakai]
  • A. Sakai chosen
    Sakai is a major Japanese city in Osaka Prefecture known historically as a prosperous port and merchant center and today as an important industrial and cultural hub.
  • B. Sakai Port
    Sakai Port is a historic Japanese harbor city area in Osaka Prefecture that has long served as a key commercial and maritime gateway.
  • C. Mahara
    Mahara is a suburban town in Sri Lanka’s Western Province, situated within the Gampaha District and known for its residential communities and local institutions.
  • D. Daiko Campus
    Daiko Campus is one of Nagoya University's satellite campuses in Nagoya, Japan, housing specialized faculties and research facilities.
  • E. Kindai
    Kindai is a major private university in Japan known for its comprehensive academic programs and strong research in fields such as science, engineering, and fisheries.
  • 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_69d886ca8f348190812768ea8d5055ce completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d18a0bf881908c449f499eb86495 completed April 18, 2026, 6:46 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00dc0f13c88190b55da5be40a0a476 completed May 10, 2026, 7:27 p.m.
Created at: April 10, 2026, 5:32 a.m.