Triple
T3818888
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barney Fife |
E84322
|
entity |
| Predicate | notableGag |
P52455
|
FINISHED |
| Object | keeps single bullet in shirt pocket |
—
|
LITERAL 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: keeps single bullet in shirt pocket | Statement: [Barney Fife, notableGag, keeps single bullet in shirt pocket]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableGag Context triple: [Barney Fife, notableGag, keeps single bullet in shirt pocket]
-
A.
notableGaffe
Indicates that an entity is known for having made a significant mistake, blunder, or embarrassing error.
-
B.
notableShow
Indicates that a show is especially prominent, distinguished, or significant in some noteworthy way.
-
C.
notableGate
Indicates that a gate is recognized as significant, prominent, or noteworthy in some context.
-
D.
notableFact
Indicates that there exists a particularly significant or noteworthy fact or piece of information associated with the subject.
-
E.
notableFor
Indicates that an entity is especially recognized or distinguished for a particular quality, achievement, characteristic, or role.
- F. None of above. chosen
Provenance (4 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee74a2bc081909b237df8b1e27653 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef18748648190b85e62f7796ff4b4 |
completed | March 9, 2026, 4:12 p.m. |
Created at: March 9, 2026, 3:17 p.m.