Triple
T9502536
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony α1 |
E229179
|
entity |
| Predicate | stabilizationCompensation |
P88978
|
FINISHED |
| Object | up to 5.5 stops |
—
|
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: up to 5.5 stops | Statement: [Sony α1, stabilizationCompensation, up to 5.5 stops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: stabilizationCompensation Context triple: [Sony α1, stabilizationCompensation, up to 5.5 stops]
-
A.
dragCompensation
Indicates that one entity adjusts or counteracts the drag force experienced by another entity or system.
-
B.
stabilizedBy
Indicates that an entity’s state, structure, or behavior is made more steady, secure, or resistant to change through the influence or support of another entity.
-
C.
stabilizationOutcome
Indicates the result or state achieved after a stabilization process has been applied to something.
-
D.
compensationMechanism
Indicates a relationship where one entity provides payment, benefits, or other forms of recompense to another in return for a loss, service, or obligation.
-
E.
stabilityPolicy
Indicates that a policy defines or influences the conditions under which a system, process, or arrangement remains stable over time.
- 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_69ca847611c48190a28c028644198c75 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983ea6048190a2d7924c8e6d1fbc |
completed | April 1, 2026, 10:12 p.m. |
| PD | Predicate disambiguation | batch_69cca5651a588190a3cfebe249a223e5 |
completed | April 1, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69cca8c6b0f081908334d6c7cf80e03c |
completed | April 1, 2026, 5:10 a.m. |
Created at: March 30, 2026, 7:57 p.m.