Triple
T22377649
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spinario |
E553189
|
entity |
| Predicate | poseFocus |
P147424
|
FINISHED |
| Object | intense focus on the act of removing a thorn |
—
|
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: intense focus on the act of removing a thorn | Statement: [Spinario, poseFocus, intense focus on the act of removing a thorn]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: poseFocus Context triple: [Spinario, poseFocus, intense focus on the act of removing a thorn]
-
A.
focalLength
Indicates the distance between a lens or mirror and its focal point, determining how strongly it converges or diverges light.
-
B.
hasDigitalFocus
Indicates that an entity is primarily oriented toward or centered on digital technologies, channels, or activities.
-
C.
typicalBackFocus
Indicates a relationship where attention, emphasis, or focus is characteristically directed toward the back or rear part of something.
-
D.
autofocusPoints
Indicates the relationship between a camera (or imaging device) and the specific focus points it can automatically select or use for focusing.
-
E.
partCFocus
Indicates that a specific part or component of an entity is the primary focus or point of attention in a given 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f158292d80819094f474c0e9e14caf |
completed | April 29, 2026, 1 a.m. |
| PD | Predicate disambiguation | batch_69e73011e6388190a05edf137f488441 |
completed | April 21, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e7342e9a0081909257210a81c96b29 |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 8:45 p.m.