Triple
T1239920
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UN General Assembly Resolution 38/7 |
E26634
|
entity |
| Predicate | characterizesAs |
P13138
|
FINISHED |
| Object | a flagrant violation of international law |
—
|
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: a flagrant violation of international law | Statement: [UN General Assembly Resolution 38/7, characterizesAs, a flagrant violation of international law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterizesAs Context triple: [UN General Assembly Resolution 38/7, characterizesAs, a flagrant violation of international law]
-
A.
characterizedBy
Indicates that one entity possesses a defining quality, feature, or attribute expressed by another entity.
-
B.
recognizedAs
Indicates that one entity is acknowledged or accepted as having the identity, role, status, or classification of another entity.
-
C.
legalCharacterization
chosen
Indicates how an action, event, or situation is classified or characterized under a specific legal framework or set of laws.
-
D.
character2
Indicates that a second character entity is involved in the relationship or context defined by the predicate.
-
E.
character1
Indicates that the subject is identified as the first or primary character in a narrative or context.
- 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_69a4948689d08190b3a4a3f388c02148 |
completed | March 1, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69a4bf41c5d08190b07adbdb24d35a76 |
completed | March 1, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69a4bb696a38819095845c84f0241287 |
completed | March 1, 2026, 10:19 p.m. |
Created at: March 1, 2026, 7:47 p.m.