Triple
T38071780
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Winter Soldier Program |
E950603
|
entity |
| Predicate | weaponizedAsset |
P60876
|
FINISHED |
| Object | Winter Soldier |
—
|
NE NERFINISHED |
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: Winter Soldier | Statement: [Winter Soldier Program, weaponizedAsset, Winter Soldier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weaponizedAsset Context triple: [Winter Soldier Program, weaponizedAsset, Winter Soldier]
-
A.
weaponizedAs
chosen
Indicates that something has been adapted, modified, or used for the purpose of causing harm, damage, or coercion, effectively turning it into a weapon.
-
B.
laterWeaponizedBy
Indicates that something was subsequently developed, adapted, or used as a weapon by a specified agent or group.
-
C.
enemyMilitaryAsset
Indicates that one entity is a military asset belonging to or controlled by an enemy force relative to the other entity.
-
D.
weaponOfInterest
Indicates that an entity is a weapon that is specifically relevant, notable, or targeted for attention within a given context or scenario.
-
E.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
- 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_69f76f02a6c48190a94f3c0b3ee90cf2 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fcc7338120819081cb46547d60f2cb |
completed | May 7, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69fcc58566a0819082d5ea36e03bf0c6 |
completed | May 7, 2026, 5:01 p.m. |
Created at: May 3, 2026, 4:21 p.m.