Triple
T32073481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Force de frappe |
E819077
|
entity |
| Predicate | targetingDoctrine |
P195549
|
FINISHED |
| Object | countervalue |
—
|
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: countervalue | Statement: [Force de frappe, targetingDoctrine, countervalue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetingDoctrine Context triple: [Force de frappe, targetingDoctrine, countervalue]
-
A.
targetsUseCase
Indicates that one entity is aimed at or designed to address a particular use case associated with another entity.
-
B.
targetedRegime
Indicates that an entity intentionally directed actions, policies, or operations against a particular governing regime.
-
C.
paradigmTargeted
Indicates that an action, method, or influence is specifically directed toward or focused on a particular paradigm.
-
D.
bindingTarget
Indicates that one entity serves as the specific object, site, or counterpart to which another entity binds or is bound.
-
E.
targetsComponent
Indicates that one entity is specifically directed at, aimed at, or intended to affect a particular component of another entity or system.
- 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_69f348fecc088190af1470afe5a969f0 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fdd92396788190ae1424bc1ae55844 |
completed | May 8, 2026, 12:37 p.m. |
| PD | Predicate disambiguation | batch_69fdd678f40481909a717a2daec83b36 |
completed | May 8, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69fdd922d73c81908ad3faade247ec16 |
completed | May 8, 2026, 12:37 p.m. |
Created at: May 1, 2026, 12:23 a.m.