Triple
T30774063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fujifilm X-H2 |
E783609
|
entity |
| Predicate | afPoints |
P170115
|
FINISHED |
| Object | 425 points |
—
|
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: 425 points | Statement: [Fujifilm X-H2, afPoints, 425 points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: afPoints Context triple: [Fujifilm X-H2, afPoints, 425 points]
-
A.
leafPoints
Indicates that one leaf or leaf-like structure is oriented or directed toward, or points at, another entity.
-
B.
points
Indicates that one entity directs attention, focus, or a physical/abstract indication toward another entity or location.
-
C.
anchorPoint
Indicates a fixed reference position used to attach, align, or position one entity relative to another.
-
D.
labelPoints
Indicates assigning descriptive or identifying labels to specific points within a dataset, structure, or space.
-
E.
tryPoints
Indicates an attempt by one entity to score or gain points, typically through some action or effort directed toward achieving those points.
- 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_69f224b1519081908b9db003fd2073e0 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68fe016688190b2fe1f6931ee1e48 |
completed | May 2, 2026, 11:59 p.m. |
| PD | Predicate disambiguation | batch_69f686140aa08190a35f62572b2db9b6 |
completed | May 2, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69f68848ad348190a2fb6e841dcfdb7d |
completed | May 2, 2026, 11:27 p.m. |
Created at: April 29, 2026, 8:40 p.m.