Triple
T21332413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Librarian |
E525938
|
entity |
| Predicate | creator |
P184
|
FINISHED |
| Object | David Titcher |
—
|
NE NERFINISHED |
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: David Titcher | Statement: [The Librarian, creator, David Titcher]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: David Titcher Context triple: [The Librarian, creator, David Titcher]
-
A.
David Titcher
chosen
David Titcher is a screenwriter and producer best known for creating and writing the fantasy-adventure franchise "The Librarian."
-
B.
Carl Tiflin
Carl Tiflin is a stern, practical ranch owner and the emotionally distant father of young Jody in John Steinbeck’s novella "The Red Pony."
-
C.
David Ditzel
David Ditzel is a computer engineer and entrepreneur best known as the founder of Transmeta and for his work on low-power, innovative microprocessor designs.
-
D.
Michael Bostick
Michael Bostick is a film producer known for his work on major Hollywood comedies and family films, including the hit movie "Bruce Almighty."
-
E.
Dennis Awtrey
Dennis Awtrey is a former American professional basketball center known for his defensive play and role as a key contributor on several NBA teams during the 1970s and early 1980s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b51b90788190a4dd823d962626da |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69ee5ba65c4081908b93d5dc6a937cb6 |
completed | April 26, 2026, 6:38 p.m. |
Created at: April 16, 2026, 4:42 p.m.