Triple
T30105960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Combine work |
E765130
|
entity |
| Predicate | hasNotableExampleBy |
P54527
|
FINISHED |
| Object | Robert Rauschenberg |
—
|
NE NERFINISHED |
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: Robert Rauschenberg | Statement: [Combine work, hasNotableExampleBy, Robert Rauschenberg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNotableExampleBy Context triple: [Combine work, hasNotableExampleBy, Robert Rauschenberg]
-
A.
hasNotableUseExample
Indicates that there exists a particularly significant or illustrative example of how something is used.
-
B.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
C.
notableExampleBy
chosen
Indicates that something serves as a prominent or illustrative example provided or created by a particular entity.
-
D.
hasNonExample
Indicates that something is associated with an instance that explicitly does not satisfy or illustrate a given concept, rule, or category.
-
E.
notableExampleAt
Indicates that something serves as a prominent or illustrative example of something else in a particular context or location.
- 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_69f22475ad7c8190be7f9541044a0bbb |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_6a001adc8c108190ab3a43f6415e2be3 |
completed | May 10, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_6a001a290330819097c2c3123f9014b4 |
completed | May 10, 2026, 5:39 a.m. |
Created at: April 29, 2026, 7:09 p.m.