Triple
T32615361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Facial Action Coding System |
E833769
|
entity |
| Predicate | typicalNumberOfActionUnits |
P205117
|
FINISHED |
| Object | about 30 to 40 |
—
|
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: about 30 to 40 | Statement: [Facial Action Coding System, typicalNumberOfActionUnits, about 30 to 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfActionUnits Context triple: [Facial Action Coding System, typicalNumberOfActionUnits, about 30 to 40]
-
A.
faceExpression
Indicates the specific facial expression an entity is displaying, capturing its visible emotional or expressive state.
-
B.
numberOfFaces
Indicates the relationship that specifies how many faces a given object or entity has.
-
C.
faceCharacteristics
Indicates a relationship where specific attributes or features are associated with a face or facial appearance.
-
D.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
E.
facialMarkings
Indicates that one entity has distinctive marks, patterns, or features on its face in relation to another entity or context.
- F. None of above. chosen
Provenance (4 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_69f3492bfa648190b6ae472074634e29 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a0379f0cbe481909b4b8fc6cbe297f0 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037cab06288190b093935f235ddff2 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:06 a.m.