Triple

T11023096
Position Surface form Disambiguated ID Type / Status
Subject Uta Hagen E260541 entity
Predicate givenName P17 FINISHED
Object Uta E794115 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: Uta | Statement: [Uta Hagen, givenName, Uta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Uta
Context triple: [Uta Hagen, givenName, Uta]
  • A. Uta chosen
    Uta is a central character in John Irving’s novel "The 158-Pound Marriage," depicted as a complex, emotionally conflicted woman involved in an experimental partner-swapping arrangement.
  • B. Hatohobei
    Hatohobei is a small, remote coral island state of Palau in the western Pacific Ocean, also known as Tobi.
  • C. Ukiha
    Ukiha is a small city in southwestern Japan known for its rural landscapes, fruit orchards, and traditional townscapes.
  • D. Suwawa
    Suwawa is an Austronesian language spoken by the Suwawa people in the northern part of Sulawesi, Indonesia.
  • E. Shumshu
    Shumshu is a small, strategically significant volcanic island at the northern end of the Kuril Islands chain, near the Kamchatka Peninsula.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797bd88188190a644adc9283cabb8 completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3750917d481909e73de0bfae27827 completed April 18, 2026, 12:11 p.m.
Created at: April 8, 2026, 9:25 p.m.