Triple
T8894775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Ubu |
E211778
|
entity |
| Predicate | hasSubjectCharacteristic |
P662
|
FINISHED |
| Object | ambiguous |
—
|
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: ambiguous | Statement: [Portrait of Ubu, hasSubjectCharacteristic, ambiguous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSubjectCharacteristic Context triple: [Portrait of Ubu, hasSubjectCharacteristic, ambiguous]
-
A.
hasRoleCharacteristic
Indicates that an entity possesses a specific characteristic, quality, or attribute associated with a particular role.
-
B.
hasCourseCharacteristic
Indicates that a course possesses or is associated with a particular characteristic, feature, or attribute.
-
C.
hasTypicalSubject
Indicates that something is commonly or characteristically used as the subject (agent or topic) of a given relation or action.
-
D.
hasPerformerCharacteristic
Indicates that a performer possesses a particular attribute, quality, or characteristic.
-
E.
characterizedBy
chosen
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another 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_69ca83918d3081909b326fa3750cb8c8 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc61be2c2081908f39cccdc149872d |
completed | April 1, 2026, 12:07 a.m. |
| PD | Predicate disambiguation | batch_69cc5c2aec04819093c932fe51c0f08d |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:54 p.m.