Triple
T3843355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dennis Franz |
E93505
|
entity |
| Predicate | notableTelevisionGenre |
P20471
|
FINISHED |
| Object | police procedural |
—
|
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: police procedural | Statement: [Dennis Franz, notableTelevisionGenre, police procedural]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableTelevisionGenre Context triple: [Dennis Franz, notableTelevisionGenre, police procedural]
-
A.
notableProgramType
chosen
Indicates that the subject is recognized for or associated with a particular type or category of program.
-
B.
notableSeries
Indicates that an entity is a significant or well-known installment within a particular series or franchise.
-
C.
notableTelevisionProduction
Indicates that the subject is significantly associated with the creation or production of the referenced television work.
-
D.
notableProductionType
Indicates that the subject is particularly known for producing or creating instances of the specified type.
-
E.
notableOriginalSeries
Indicates that an entity is recognized as a significant or distinguished original series associated with another entity (such as a platform, creator, or franchise).
- F. None of above.
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_69aed96ce578819084ab16e3439976c9 |
completed | March 9, 2026, 2:30 p.m. |
| NER | Named-entity recognition | batch_69aeebb4fd308190a636ba9dbbe57ed6 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee74dcecc819098285483ec721b40 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:18 p.m.