Triple
T26942546
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yondu Udonta |
E678558
|
entity |
| Predicate | weaponControlMethod |
P161346
|
FINISHED |
| Object | whistling |
—
|
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: whistling | Statement: [Yondu Udonta, weaponControlMethod, whistling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: weaponControlMethod Context triple: [Yondu Udonta, weaponControlMethod, whistling]
-
A.
weaponControl
Indicates that one entity has authority over, access to, or the ability to direct the use of a weapon associated with another entity.
-
B.
armsControl
Indicates a relationship where parties engage in limiting, regulating, or reducing weapons and military capabilities, often through agreements or treaties.
-
C.
enablesWeapon
Indicates that one entity provides the capability for another entity to use, activate, or access a weapon.
-
D.
weaponUsedIn
Indicates that a particular weapon is employed or involved in carrying out a specific event or action.
-
E.
weaponMount
Indicates that one entity serves as a mounting point or support structure for attaching or holding a weapon on another entity.
- 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_69eeeb4d69588190a7c912164a1c37b3 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f620822d6081908e38814f5a1c0931 |
completed | May 2, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69f611af72ac819094598dd2530d7411 |
completed | May 2, 2026, 3:01 p.m. |
| PDg | Predicate description generation | batch_69f6125e54e0819088ee33a20efcc9e6 |
completed | May 2, 2026, 3:03 p.m. |
Created at: April 27, 2026, 6:19 a.m.