Triple
T615280
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paveway series guided bombs |
E12189
|
entity |
| Predicate | targetIlluminationBy |
P5496
|
FINISHED |
| Object | airborne laser designator |
—
|
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: airborne laser designator | Statement: [Paveway series guided bombs, targetIlluminationBy, airborne laser designator]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetIlluminationBy Context triple: [Paveway series guided bombs, targetIlluminationBy, airborne laser designator]
-
A.
targetArea
Indicates the specific area or region that is the intended focus or destination of an action or effect.
-
B.
lightSourceFor
chosen
Indicates that one entity serves as the source of illumination for another entity.
-
C.
target
Indicates that one entity is the intended object, goal, or focus of another entity’s action or attention.
-
D.
hasLighting
Indicates that one entity is equipped with, contains, or is characterized by a particular type or configuration of lighting.
-
E.
designLuminosity
Indicates the specified luminosity level or brightness characteristics that something is designed or intended to have.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e0b438881909ad515adf7a4eb79 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfbcbf88190a854921dc531eba8 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.