Triple

T17654043
Position Surface form Disambiguated ID Type / Status
Subject Howard-Gabel E429571 entity
Predicate writtenForm P2203 FINISHED
Object Howard-Gabel NE NERFINISHED

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: Howard-Gabel | Statement: [Howard-Gabel, writtenForm, Howard-Gabel]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Howard-Gabel
Context triple: [Howard-Gabel, writtenForm, Howard-Gabel]
  • A. Howard-Gabel chosen
    Howard-Gabel is a surname associated with individuals such as Theodore Norman Howard-Gabel.
  • B. Gabler
    Gabler is a surname most notably associated with Milt Gabler, an influential American record producer and songwriter in jazz and popular music.
  • C. Guare
    Guare is a surname most notably associated with American playwright John Guare, known for works such as "Six Degrees of Separation."
  • D. Vanderhof
    Vanderhof is the surname of the eccentric, free-spirited family at the center of the classic American play and film "You Can't Take It with You."
  • E. Gabbs
    Gabbs is a small, remote town in central Nevada known historically for its mining activities and desert surroundings.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d889e2c2608190b762e76d9b2262f1 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e46e3ed8b08190a00efdad9740bf6f completed April 19, 2026, 5:55 a.m.
Created at: April 10, 2026, 6:05 a.m.