Triple
T15616639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebecca Howe |
E375429
|
entity |
| Predicate | portrayedByInMedium |
P1507
|
FINISHED |
| Object | Kirstie Alley on television |
—
|
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: Kirstie Alley on television | Statement: [Rebecca Howe, portrayedByInMedium, Kirstie Alley on television]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedByInMedium Context triple: [Rebecca Howe, portrayedByInMedium, Kirstie Alley on television]
-
A.
portrayedBy
chosen
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
B.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
-
C.
portrayedInFilmMedium
Indicates that an entity is depicted or represented within a film or cinematic work.
-
D.
portrayedByAlsoPlays
Indicates that the actor who portrays a given character also plays another specified role or character.
-
E.
portrayedByWork
Indicates that a work (such as a film, book, or artwork) depicts, represents, or portrays a particular entity.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e980b748190b43c0b650bf1e629 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda844af081909e658ebc9d9b403d |
completed | April 15, 2026, 12:23 a.m. |
Created at: April 10, 2026, 4:13 a.m.