Triple

T1505735
Position Surface form Disambiguated ID Type / Status
Subject Terry Porter E33896 entity
Predicate fullName P16 FINISHED
Object Terry Porter E33896 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: Terry Porter | Statement: [Terry Porter, fullName, Terry Porter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Terry Porter
Context triple: [Terry Porter, fullName, Terry Porter]
  • A. Terry Porter chosen
    Terry Porter is a former NBA point guard best known for his leadership and clutch play with the Portland Trail Blazers during their successful late-1980s and early-1990s seasons.
  • B. Terry Davis
    Terry Davis is a British Labour politician who served as Secretary General of the Council of Europe and was previously a long-standing Member of Parliament in the UK.
  • C. Phillip Terry
    Phillip Terry was an American film and television actor active from the 1930s to the 1960s, known for his supporting roles in Hollywood productions.
  • D. Merv Jackson
    Merv Jackson was a professional basketball guard best known for his key role with the Utah Stars in the American Basketball Association (ABA) during the early 1970s.
  • E. Terry McAulay
    Terry McAulay is a former National Football League official who served as a referee in multiple Super Bowls and later became a rules analyst for television broadcasts.
  • 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_69a885f352a4819099b24ff15489dede completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a88734508481909378bb3e86e13323 completed March 4, 2026, 7:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad308dba548190b81999135210cc96 completed March 8, 2026, 8:17 a.m.
Created at: March 4, 2026, 7:24 p.m.