Triple
T9502550
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony α1 |
E229179
|
entity |
| Predicate | supportsEyeAFForAnimals |
P88981
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Sony α1, supportsEyeAFForAnimals, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsEyeAFForAnimals Context triple: [Sony α1, supportsEyeAFForAnimals, true]
-
A.
supportsWildlife
Indicates that one entity provides conditions, resources, or protection that help sustain or benefit wildlife associated with another entity.
-
B.
usesLiveAnimals
Indicates that one entity employs or incorporates live animals in performing an action, service, process, or activity involving another entity.
-
C.
supportsBirdlife
Indicates that one entity provides conditions or resources that help sustain or benefit bird life associated with another entity.
-
D.
usesCaninesFor
Indicates a relationship where an entity employs or relies on its canine teeth for a particular function or activity.
-
E.
usedAnimal
Indicates that one entity employed or exploited an animal for a particular purpose or activity.
- 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.