Triple
T10423977
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Simo Häyhä |
E245735
|
entity |
| Predicate | usedOptics |
P7239
|
FINISHED |
| Object | iron sights |
—
|
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: iron sights | Statement: [Simo Häyhä, usedOptics, iron sights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedOptics Context triple: [Simo Häyhä, usedOptics, iron sights]
-
A.
usesOpticsType
chosen
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
B.
usesLensBrand
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
C.
opticalDesign
Indicates a relationship where one entity is responsible for creating, specifying, or defining the optical configuration or characteristics of another entity.
-
D.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
E.
originalLens
Indicates that one lens is the initial or source lens from which another lens or lens configuration is derived or referenced.
- 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_69d381bf3dc08190bf35a2643e4e8f22 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4ea2de4d48190aee65b3f6ec3cc48 |
completed | April 7, 2026, 11:27 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb9d3648190aaabed901f22a8c0 |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:12 p.m.