Triple
T30949538
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-S20 |
E788495
|
entity |
| Predicate | subjectDetectionTypes |
P151609
|
FINISHED |
| Object | human face and eye |
—
|
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: human face and eye | Statement: [Fujifilm X-S20, subjectDetectionTypes, human face and eye]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectDetectionTypes Context triple: [Fujifilm X-S20, subjectDetectionTypes, human face and eye]
-
A.
subjectType
Indicates the classification or category that defines what kind of entity the subject is.
-
B.
subjectCategories
Indicates that an entity is associated with one or more subject-based categories or classifications.
-
C.
aimsToDetect
chosen
Indicates an intention or designed purpose to discover, identify, or recognize the presence or characteristics of something.
-
D.
seeType
Indicates that one entity observes, recognizes, or visually perceives another entity of a particular type or category.
-
E.
detectorType
Indicates the specific kind or category of detector associated with an entity or measurement.
- F. None of above.
Provenance (3 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_69f224c180f88190ad177372ee02b7e2 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: April 29, 2026, 8:53 p.m.