Triple
T2770663
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UN Special Commission |
E61446
|
entity |
| Predicate | typeOfWeaponsTargeted |
P9724
|
FINISHED |
| Object | chemical weapons |
—
|
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: chemical weapons | Statement: [UN Special Commission, typeOfWeaponsTargeted, chemical weapons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfWeaponsTargeted Context triple: [UN Special Commission, typeOfWeaponsTargeted, chemical weapons]
-
A.
weaponsUsed
Indicates that one entity employed or utilized another entity as a weapon in carrying out an action or event.
-
B.
involvesWeaponType
chosen
Indicates that the relationship or action includes the use, presence, or association of a specific type or category of weapon.
-
C.
weaponUsedAgainst
Indicates that a particular weapon or instrument is employed in an act of aggression, attack, or harm directed toward a specific target or entity.
-
D.
typicalWeapon
Indicates that the object is a weapon commonly or characteristically used by the subject.
-
E.
typeOfWeaponsProduced
Indicates the specific categories or kinds of weapons that are manufactured or produced by an entity.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfed608819080988e93df7bdf7c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.