Triple

T16386682
Position Surface form Disambiguated ID Type / Status
Subject Dana Barrett E397940 entity
Predicate neighborOf P350 FINISHED
Object Louis Tully E406923 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: Louis Tully | Statement: [Dana Barrett, neighborOf, Louis Tully]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Tully
Context triple: [Dana Barrett, neighborOf, Louis Tully]
  • A. Louis Tully chosen
    Louis Tully is a nerdy, well-meaning accountant and neighbor of Dana Barrett who becomes a comedic, possessed pawn of Gozer in the Ghostbusters films.
  • B. William Mulloy
    William Mulloy was an American archaeologist best known for his pioneering restoration and conservation work on the moai and ceremonial sites of Easter Island (Rapa Nui).
  • C. George Shively
    George Shively was an early 20th-century Negro league outfielder known for his speed, strong defense, and key role on several prominent Black baseball teams.
  • D. Eugene Roche
    Eugene Roche was an American character actor known for his prolific work in film and television, often playing affable or comedic supporting roles.
  • E. Charles Coleman
    Charles Coleman was an Australian-born character actor known for his frequent roles as butlers and valets in numerous Hollywood films during the early to mid-20th century.
  • 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_69d87f2880b48190ae1a9673a3bbef80 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e3263d260081909db9ac6016d5738a completed April 18, 2026, 6:35 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0170db6c6881908f5670c8282f4097 completed May 11, 2026, 6:02 a.m.
Created at: April 10, 2026, 5:08 a.m.