Triple

T10565949
Position Surface form Disambiguated ID Type / Status
Subject Victor Lawson E249349 entity
Predicate givenName P17 FINISHED
Object Victor E30470 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: Victor | Statement: [Victor Lawson, givenName, Victor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Victor
Context triple: [Victor Lawson, givenName, Victor]
  • A. Victor
    Victor is a central character in the TV series "Dollhouse," known as one of the programmable "Actives" whose identity and memories are repeatedly altered for various missions.
  • B. Victor
    Victor is a character in Gregory Benford’s science fiction novel "Timescape," which explores time communication and ecological catastrophe.
  • C. Victor chosen
    Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
  • D. Victor
    Victor was a prominent early 20th-century record label known for producing and distributing influential jazz and popular music recordings.
  • E. Victor
    Victor is a British Cold War–era jet aircraft that served as both a strategic bomber and later an aerial refueling tanker for the Royal Air Force.
  • 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_69d381c8bd708190acf3d275c908251e completed April 6, 2026, 9:50 a.m.
NER Named-entity recognition batch_69d5272ce78c8190bf3227053ef88a48 completed April 7, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69d9349bb7748190b5afb492e78d1128 completed April 10, 2026, 5:34 p.m.
Created at: April 6, 2026, 12:36 p.m.