Triple
T11760654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Sergeant |
E279645
|
entity |
| Predicate | authorOfSourceWork |
P2353
|
FINISHED |
| Object | Dennis Murphy |
E993756
|
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: Dennis Murphy | Statement: [The Sergeant, authorOfSourceWork, Dennis Murphy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dennis Murphy Context triple: [The Sergeant, authorOfSourceWork, Dennis Murphy]
-
A.
Dennis Murphy
Dennis Murphy was an American sports entrepreneur best known for co-founding several upstart professional leagues, including the American Basketball Association.
-
B.
Dennis Murphy
Dennis Murphy is an American television journalist best known as a longtime correspondent and host for NBC's newsmagazine program Dateline NBC.
-
C.
Dennis Murphy
chosen
Dennis Murphy was a screenwriter known for his work on the film "The Sergeant."
-
D.
Dennis McNulty
Dennis McNulty is a designer known for his work on the wooden roller coaster Shivering Timbers.
-
E.
Don Murphy
Don Murphy is an American film producer best known for helping launch and produce the live-action Transformers film franchise.
- 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_69d6ab01038c819080714901502c84fc |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a52386708190b744746a2db37495 |
completed | April 10, 2026, 7:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f668479b188190ae720e77fbf6897f |
completed | May 2, 2026, 9:10 p.m. |
Created at: April 8, 2026, 9:41 p.m.