Triple

T12142765
Position Surface form Disambiguated ID Type / Status
Subject Gunter, Texas E289229 entity
Predicate abbreviation P43 FINISHED
Object Gunter E563073 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: Gunter | Statement: [Gunter, Texas, abbreviation, Gunter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gunter
Context triple: [Gunter, Texas, abbreviation, Gunter]
  • A. Gunter chosen
    Gunter is a flamboyant, energetic pig who serves as one of the standout comedic performers in the animated musical film "Sing 2."
  • B. Gunner
    Gunner is a masculine given name and surname of English origin, often associated with strength and warrior-like qualities.
  • C. Reubell
    Reubell is a French surname most notably associated with Jean-François Reubell, a prominent political figure during the French Revolution and a member of the Directory.
  • D. Sperrle
    Sperrle is a German surname most notably borne by Hugo Sperrle, a senior Luftwaffe field marshal during World War II.
  • E. Gunta
    Gunta is a given name most notably borne by Gunta Stölzl, a pioneering textile artist and the only female master at the Bauhaus school.
  • 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_69d6ab4c6710819097a9d228382dde43 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915a9838081909622cc14df2a2582 completed April 10, 2026, 3:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f69501348190a9ac090c7db37c20 completed May 2, 2026, 1:05 p.m.
Created at: April 8, 2026, 9:49 p.m.