Triple
T30481931
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony FE 85mm f/1.4 GM |
E775609
|
entity |
| Predicate | useOnAPSCCropEquivalent |
P169493
|
FINISHED |
| Object | about 127.5 mm |
—
|
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: about 127.5 mm | Statement: [Sony FE 85mm f/1.4 GM, useOnAPSCCropEquivalent, about 127.5 mm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: useOnAPSCCropEquivalent Context triple: [Sony FE 85mm f/1.4 GM, useOnAPSCCropEquivalent, about 127.5 mm]
-
A.
usesCrop
Indicates that one entity employs or applies a particular crop for a specific purpose or function.
-
B.
isCrop
Indicates that an entity functions as or is classified as an agricultural crop.
-
C.
includesCropType
Indicates that an entity contains or encompasses a specific type of crop within its scope or composition.
-
D.
includesCrop
Indicates that one entity (such as a field, farm, or agricultural area) contains or has within it a specified crop.
-
E.
hasCropSpecies
Indicates that a particular location, field, or agricultural system is associated with or used to cultivate a specified crop species.
- 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_69f22497341481909c21ba329fadaa6b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68742cc6481908be525603fb6ba97 |
completed | May 2, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69f678d2196c8190b9d0d2fcd47cc539 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67d31cc60819084f64bd056e1ea4d |
completed | May 2, 2026, 10:39 p.m. |
Created at: April 29, 2026, 8:12 p.m.