Triple
T13610105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "I'll Be There for You" |
E325164
|
entity |
| Predicate | hasAssociatedShowGenre |
P73830
|
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: ["I'll Be There for You", hasAssociatedShowGenre, sitcom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedShowGenre Context triple: ["I'll Be There for You", hasAssociatedShowGenre, sitcom]
-
A.
hasGenreInSeries
Indicates that a particular genre is associated with, or applies to, a work as it appears within a specific series.
-
B.
hasGenreInRoles
Indicates that an entity participates in roles associated with a particular genre or set of genres.
-
C.
associatedShowType
chosen
Indicates a relationship where one entity is linked to the type or category of show with which it is associated.
-
D.
associatedWithGenreScene
Indicates that an entity is connected or related to a particular genre scene, such as a specific stylistic or cultural subcommunity within a broader genre.
-
E.
hasGenreAsSetting
Indicates that a work’s setting is characterized by, or takes place within, a particular genre.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.