Triple
T13021978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Edna Garrett |
E326193
|
entity |
| Predicate | televisionGenreOfWork |
P83375
|
FINISHED |
| Object | sitcom |
—
|
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: sitcom | Statement: [Edna Garrett, televisionGenreOfWork, sitcom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: televisionGenreOfWork Context triple: [Edna Garrett, televisionGenreOfWork, sitcom]
-
A.
televisionWork
Indicates a relationship where a creative work is produced for, broadcast on, or primarily associated with television.
-
B.
televisionCategory
Indicates the classification or genre category assigned to a television-related entity (such as a show, channel, or program).
-
C.
tvGenre
chosen
Indicates the genre or category to which a television show or program belongs.
-
D.
televisionShow
Indicates that one entity is a television show associated with, or featured in relation to, another entity.
-
E.
televisionFilm
Indicates that the subject is a television film (a movie produced for or originally distributed via television).
- 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_69d8076cc45c81908123123f43e69266 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97ed05e9c8190a4f208662bca0602 |
completed | April 10, 2026, 10:50 p.m. |
| PD | Predicate disambiguation | batch_69d97dc39a0881908119c62e31bf6182 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:52 p.m.