Triple

T3986672
Position Surface form Disambiguated ID Type / Status
Subject Atakule E86887 entity
Predicate owner P347 FINISHED
Object Atakule GYO E86887 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: Atakule GYO | Statement: [Atakule, owner, Atakule GYO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Atakule GYO
Context triple: [Atakule, owner, Atakule GYO]
  • A. Atakule chosen
    Atakule is a prominent observation and communications tower in Ankara, Turkey, known for its panoramic city views and revolving restaurant.
  • B. Katsuragi
    Katsuragi is a city in Japan known for its location in Nara Prefecture and its historical and cultural ties to the ancient Yamato region.
  • C. Katsuragi
    Katsuragi was a late-war Imperial Japanese Navy aircraft carrier that served in the Pacific Theater during World War II.
  • D. Akizuki
    Akizuki was a Japanese Akizuki-class destroyer of the Imperial Japanese Navy that served in World War II before being sunk in the Battle off Cape Engaño in 1944.
  • E. Takanot
    Takanot are rabbinic enactments or decrees established to address communal needs and clarify or safeguard Jewish law within Rabbinic Judaism.
  • 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_69aed93fd9d4819085d3b2137d2346cb completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9fe355081909b04662ab44fe2ca completed March 9, 2026, 4:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5402bbe208190947321353c309c98 completed March 14, 2026, 11:02 a.m.
Created at: March 9, 2026, 3:33 p.m.