Triple

T2529844
Position Surface form Disambiguated ID Type / Status
Subject Port of Sakai-Semboku E56130 entity
Predicate locatedInCity P40 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: [Port of Sakai-Semboku, locatedInCity, Sakai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sakai
Context triple: [Port of Sakai-Semboku, locatedInCity, 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. Daiko Campus
    Daiko Campus is one of Nagoya University's satellite campuses in Nagoya, Japan, housing specialized faculties and research facilities.
  • C. 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.
  • D. Sakae
    Sakae is a major downtown commercial and entertainment district in Nagoya, Japan, known for its shopping, nightlife, and landmark attractions.
  • E. Kaisei Academy
    Kaisei Academy is a prestigious Japanese boys' secondary school in Tokyo known for its rigorous academics and history of producing many prominent political and intellectual leaders.
  • 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_69ab4a48e4f081908f1218d244608659 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd276930c8190bd46b52e06b7098e completed March 7, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69af2bb6bb608190845706f1a675ad1c completed March 9, 2026, 8:21 p.m.
Created at: March 6, 2026, 9:46 p.m.