Triple
T14226438
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garbo Talks |
E352627
|
entity |
| Predicate | featuresCameoOrRole |
P49662
|
FINISHED |
| Object | Greta Garbo look-alike |
—
|
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: Greta Garbo look-alike | Statement: [Garbo Talks, featuresCameoOrRole, Greta Garbo look-alike]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCameoOrRole Context triple: [Garbo Talks, featuresCameoOrRole, Greta Garbo look-alike]
-
A.
featuresCameoBy
chosen
Indicates that a work includes a brief, often special-appearance role performed by the specified person or entity.
-
B.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
C.
featuresCharacterWith
Indicates that one entity (such as a work or product) includes or presents a particular character as part of its content.
-
D.
creativeRole
Indicates that an entity holds a specific creative function or responsibility in relation to another entity, such as a work or project.
-
E.
roleCharacteristic
Indicates that a particular characteristic, quality, or attribute is associated with and helps define a given role or function.
- 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_69d8278a06e481908b5d6af0a8afe737 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6228e53c8190abbe4e2d88a7362a |
completed | April 14, 2026, 3:50 p.m. |
| PD | Predicate disambiguation | batch_69de05bf069c8190b69f00f00f5eb126 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:06 a.m.