Triple
T10960087
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jamaican Sign Language |
E258950
|
entity |
| Predicate | hasNonManualMarkers |
P96851
|
FINISHED |
| Object | facial expressions |
—
|
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: facial expressions | Statement: [Jamaican Sign Language, hasNonManualMarkers, facial expressions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonManualMarkers Context triple: [Jamaican Sign Language, hasNonManualMarkers, facial expressions]
-
A.
hasMarker
Indicates that one entity possesses, is associated with, or is identified by a specific marker.
-
B.
hasManual
Indicates that an entity is associated with a manual that provides instructions or documentation for it.
-
C.
numberOfMarkers
Indicates the quantity or count of markers associated with a given entity or context.
-
D.
hasMeasurementMarkings
Indicates that one entity bears visible measurement indicators or scale markings on its surface for quantifying something.
-
E.
hasManualLabor
Indicates that one entity performs or is responsible for physical or manual work 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_69d6aa88500c819097d7032ca578e74f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d771293c208190ac084681ed801e22 |
completed | April 9, 2026, 9:28 a.m. |
| PD | Predicate disambiguation | batch_69d72e874f48819096ffa878f90c7d5b |
completed | April 9, 2026, 4:43 a.m. |
| PDg | Predicate description generation | batch_69d7322370648190ba14cdd6fb4cdcb0 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:23 p.m.