Triple
T17713302
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AWAKE Run 1 experiments |
E441623
|
entity |
| Predicate | usesLaser |
P128688
|
FINISHED |
| Object | ionizing laser pulse to create plasma |
—
|
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: ionizing laser pulse to create plasma | Statement: [AWAKE Run 1 experiments, usesLaser, ionizing laser pulse to create plasma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesLaser Context triple: [AWAKE Run 1 experiments, usesLaser, ionizing laser pulse to create plasma]
-
A.
usesLaserType
Indicates that one entity employs or operates a specific type or category of laser in performing an action or function.
-
B.
laserColor
Indicates the color attribute associated with a laser in the relationship or action.
-
C.
usesCanons
Indicates that one entity employs or makes use of canons (such as rules, principles, or artillery pieces) in relation to another entity or context.
-
D.
laserEnergyPerShot
Indicates the amount of energy released by a laser in a single shot or pulse.
-
E.
usesMissileSystem
Indicates that one entity employs or operates a particular missile system as part of its capabilities or actions.
- 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_69d8b9ea20b48190ace88bb46b01e6a9 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e4729cebd08190872be96a26d0f7ce |
completed | April 19, 2026, 6:13 a.m. |
| PD | Predicate disambiguation | batch_69e3cde601d4819097903f471f1fe99a |
completed | April 18, 2026, 6:31 p.m. |
| PDg | Predicate description generation | batch_69e3d018227c8190b6624a2199e765e8 |
completed | April 18, 2026, 6:40 p.m. |
Created at: April 10, 2026, 10:06 a.m.