Triple
T11966579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naranjito |
E284804
|
entity |
| Predicate | hasFacialExpression |
P23736
|
FINISHED |
| Object | smiling |
—
|
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: smiling | Statement: [Naranjito, hasFacialExpression, smiling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacialExpression Context triple: [Naranjito, hasFacialExpression, smiling]
-
A.
faceExpression
chosen
Indicates the specific facial expression an entity is displaying, capturing its visible emotional or expressive state.
-
B.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
-
C.
hasExpressivity
Indicates that one entity possesses a certain level or type of expressive power, capability, or richness in representation relative to another.
-
D.
emotionDisplayed
Indicates that an entity is outwardly expressing or showing a particular emotion.
-
E.
hasSignatureSmile
Indicates that an entity is characterized by a distinctive or recognizable smile that serves as a notable or identifying feature.
- 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_69d6ab2eaeb881909f7914758f859413 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9037adf5881908abe1a4e64a71f20 |
completed | April 10, 2026, 2:04 p.m. |
| PD | Predicate disambiguation | batch_69d8bb40f30c8190a0e0719bd67542bf |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:46 p.m.