Triple
T12630327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 14 Intelligence Company |
E301621
|
entity |
| Predicate | usedUnmarkedVehicles |
P106112
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [14 Intelligence Company, usedUnmarkedVehicles, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedUnmarkedVehicles Context triple: [14 Intelligence Company, usedUnmarkedVehicles, yes]
-
A.
usesMarkedVehicles
Indicates that an entity carries out its activities or operations using vehicles that are visibly marked or identified for that purpose.
-
B.
usedPoliticalVehicle
Indicates that an entity employed a political organization, campaign, or platform as a means or instrument to achieve its goals or carry out actions.
-
C.
vehicleUsed
Indicates that a particular vehicle is utilized or employed in performing an action, event, or activity.
-
D.
intendedVehicle
Indicates that one entity is the vehicle that another entity plans or is meant to use.
-
E.
hasVehicle
Indicates that one entity possesses, owns, or is assigned a vehicle.
- 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_69d7bdeaf49c8190b13800111fa77ea3 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ae493481908f82e0d05dce20bd |
completed | April 10, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69d960b47130819097e1162ed4fc993a |
completed | April 10, 2026, 8:42 p.m. |
| PDg | Predicate description generation | batch_69d961acadb8819098de743bc951fedb |
completed | April 10, 2026, 8:46 p.m. |
Created at: April 9, 2026, 5:15 p.m.