Triple

T3681344
Position Surface form Disambiguated ID Type / Status
Subject Ghostbusters II E78117 entity
Predicate character P662 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: [Ghostbusters II, character, Louis Tully]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Louis Tully
Context triple: [Ghostbusters II, character, 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. Sylvester Keliher
    Sylvester Keliher was a prominent labor leader associated with the American Railway Union, an influential early industrial union in the United States.
  • C. Eugene Maurice
    Eugene Maurice was a 17th-century French nobleman and military commander who held the title of Count of Soissons.
  • D. Frank Fay
    Frank Fay was an American stage and film actor and vaudeville comedian, noted as an early master of stand-up comedy and for his tumultuous marriage to actress Barbara Stanwyck.
  • E. William Lanteau
    William Lanteau was an American character actor known for his supporting roles in film and television, including a notable appearance in the drama "On Golden Pond."
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc492aed481909e8986378ad283fc completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdf9f26be48190bf21b252a922ca69 completed March 21, 2026, 1:52 a.m.
Created at: March 8, 2026, 3:25 p.m.