Triple

T8366227
Position Surface form Disambiguated ID Type / Status
Subject Tama South E197132 entity
Predicate partOf P40 FINISHED
Object Tama E38268 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: Tama | Statement: [Tama South, partOf, Tama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tama
Context triple: [Tama South, partOf, Tama]
  • A. Tama chosen
    Tama is a region in western Tokyo, Japan, encompassing several suburban cities and towns that serve as residential and commercial areas for the greater Tokyo metropolis.
  • B. Tama
    Tama was a Japanese light cruiser of the Imperial Japanese Navy that served in World War II before being sunk during the Battle off Cape Engaño in 1944.
  • C. Takaro
    Takaro is a residential suburb located within the city of Palmerston North in New Zealand.
  • D. Taura
    Taura is a small municipality in the German state of Saxony, located within the administrative district of Mittelsachsen.
  • E. Totsakan
    Totsakan is the ten-headed demon king of Lanka in the Thai epic Ramakien, serving as its central villain and a key figure in Thai classical literature and performance.
  • 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_69ca82f2dbe48190aba982e75a0d94de completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb808cf80c8190941c3cc0248a5df2 completed March 31, 2026, 8:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc78c0c208190ba590c74512a4043 completed April 2, 2026, 1:34 a.m.
Created at: March 30, 2026, 6 p.m.