Triple

T11318359
Position Surface form Disambiguated ID Type / Status
Subject Paul Ford E268024 entity
Predicate name P16 FINISHED
Object Paul Ford E268024 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: Paul Ford | Statement: [Paul Ford, name, Paul Ford]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Paul Ford
Context triple: [Paul Ford, name, Paul Ford]
  • A. Paul Ford chosen
    Paul Ford was an American character actor best known for his comedic roles in mid-20th-century film and television, including his portrayal of blustery authority figures.
  • B. Daniel Ford
    Daniel Ford was a 19th-century American editor and publisher best known for shaping the influential family magazine The Youth's Companion.
  • C. Jonathan Ford
    Jonathan Ford is a senior naval officer and executive officer aboard the seaQuest DSV in the science fiction television series "seaQuest DSV."
  • D. David Ford
    David Ford is a Northern Irish politician and former leader of the Alliance Party who became the first person to serve as Northern Ireland’s Minister of Justice after the devolution of policing and justice powers.
  • E. David Ford
    David Ford was an American actor best known for his work in mid-20th-century film and television, including a leading role in the historical film "1776."
  • 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_69d6aaca5c24819083db46a30d86cb34 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e9de875481908acfa56015d4b46f completed April 9, 2026, 6:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69e525d3160c8190b58c5c04a66b3e3e completed April 19, 2026, 6:58 p.m.
Created at: April 8, 2026, 9:32 p.m.