Triple
T10453864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Master |
E246500
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Peter McNulty |
E356549
|
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: Peter McNulty | Statement: [The Master, editedBy, Peter McNulty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Peter McNulty Context triple: [The Master, editedBy, Peter McNulty]
-
A.
Peter McNulty
chosen
Peter McNulty is a film editor known for his work on feature films including the military drama "Megan Leavey."
-
B.
Patrick McNulty
Patrick McNulty is the central character in the Twilight Zone episode "A Kind of Stopwatch," a talkative and meddlesome man who acquires a magical stopwatch that can freeze time.
-
C.
Sean McNulty
Sean McNulty is a minor character in the television series "The Wire," known primarily as one of detective Jimmy McNulty's sons.
-
D.
Tony McNulty
Tony McNulty is a British Labour politician who served as Member of Parliament and held ministerial roles including Minister of State for Security, Counter-Terrorism, Crime and Policing.
-
E.
Matthew McNulty
Matthew McNulty is a British actor known for his work in film and television, including roles in series like "Misfits," "The Mill," and "Versailles."
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe0d73d48190acb687b96918e0cf |
completed | April 7, 2026, 12:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb028c0788190ae8d6750f2f9634e |
completed | April 14, 2026, 9:22 p.m. |
Created at: April 6, 2026, 12:17 p.m.