Triple

T9559013
Position Surface form Disambiguated ID Type / Status
Subject Mauke E230621 entity
Predicate hasSettlement P1068 FINISHED
Object Oiretumu E806525 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: Oiretumu | Statement: [Mauke, hasSettlement, Oiretumu]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oiretumu
Context triple: [Mauke, hasSettlement, Oiretumu]
  • A. Oiretumu chosen
    Oiretumu is the main village and administrative center of the island of Mauke in the Cook Islands.
  • B. Nakoruru
    Nakoruru is a popular Samurai Shodown character known as a nature-loving Ainu shrine maiden who fights alongside her hawk and wolf companions.
  • C. Oirats
    The Oirats are a confederation of western Mongolic tribes historically known for their powerful nomadic states in Central Asia and significant role in regional politics and warfare.
  • D. Temanoku
    Temanoku is a small settlement located on Nonouti Atoll in the Republic of Kiribati in the central Pacific Ocean.
  • E. Kudanshita
    Kudanshita is a district and major subway station area in central Tokyo known for its proximity to the Imperial Palace, Yasukuni Shrine, and several universities and office buildings.
  • 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_69ca847e53a88190a60eed7e02257f10 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd994a7e9c8190b68883c2ea45aa1a completed April 1, 2026, 10:16 p.m.
NED1 Entity disambiguation (via context triple) batch_69d17900ae2c819087a83f6c74a59afc completed April 4, 2026, 8:48 p.m.
Created at: March 30, 2026, 8:03 p.m.