Triple

T7714397
Position Surface form Disambiguated ID Type / Status
Subject Love Field E174844 entity
Predicate editedBy P1954 FINISHED
Object O. Nicholas Brown E147538 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: O. Nicholas Brown | Statement: [Love Field, editedBy, O. Nicholas Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: O. Nicholas Brown
Context triple: [Love Field, editedBy, O. Nicholas Brown]
  • A. O. Nicholas Brown chosen
    O. Nicholas Brown is an editor known for his work on the publication titled "The Accused."
  • B. Jonathan Brown
    Jonathan Brown is a cinematographer best known for his work on major studio comedies and mainstream Hollywood films, including the 2006 reboot of The Pink Panther.
  • C. John Nicholas Brown I
    John Nicholas Brown I was a prominent 19th-century American businessman and philanthropist from the influential Brown family of Rhode Island.
  • D. Michael Henry Brown
    Michael Henry Brown is a screenwriter best known for his work on the crime thriller film "In Too Deep."
  • E. Nicholas Proctor Brown
    Nicholas Proctor Brown was a mountaineer known for making the first ascent of the Dent du Géant in the Mont Blanc massif of the Alps.
  • 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_69c6995c463c8190a14458036249d419 completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c702ca8f048190a6ea27b8cee2f93e completed March 27, 2026, 10:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8acd5e32c8190869834b21aeae8a7 completed March 29, 2026, 4:38 a.m.
Created at: March 27, 2026, 4:04 p.m.