Triple
T28309492
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | No. 4 Mk I |
E713957
|
entity |
| Predicate | primarySightingSystem |
P81647
|
FINISHED |
| Object | aperture rear sight |
—
|
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: aperture rear sight | Statement: [No. 4 Mk I, primarySightingSystem, aperture rear sight]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySightingSystem Context triple: [No. 4 Mk I, primarySightingSystem, aperture rear sight]
-
A.
sightingSystem
chosen
Indicates a relationship where a system is used to detect, observe, or track targets or objects, typically for monitoring or aiming purposes.
-
B.
primaryAISpecies
Indicates that one species is the main or dominant species associated with a particular AI system or AI-related context.
-
C.
primaryIdentification
Indicates that one identifier is the main or officially recognized identification for an entity among possibly multiple identifiers.
-
D.
sightingState
Indicates the current status or condition of a reported sighting within its tracking or verification process.
-
E.
primaryDetectorType
Indicates the main kind or category of detector that is used as the primary sensing or measurement component in a given context.
- 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_69efb5256afc8190b9322d25c3ae6320 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a00233e2170819084bee0c8f74cc1a4 |
completed | May 10, 2026, 6:18 a.m. |
| PD | Predicate disambiguation | batch_6a0022943fd08190b73007f080d5971d |
completed | May 10, 2026, 6:15 a.m. |
Created at: April 27, 2026, 11:39 p.m.