Triple
T3781627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | flag of Kuwait |
E85430
|
entity |
| Predicate | blackRepresents |
P14358
|
FINISHED |
| Object | defeat of enemies in battle |
—
|
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: defeat of enemies in battle | Statement: [flag of Kuwait, blackRepresents, defeat of enemies in battle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blackRepresents Context triple: [flag of Kuwait, blackRepresents, defeat of enemies in battle]
-
A.
blueRepresents
Indicates that the color blue is used to symbolize, denote, or stand for a particular concept, state, or category in a given context.
-
B.
yellowRepresents
Indicates that the color yellow is used to symbolize, denote, or stand for a particular entity, concept, or state in a given context.
-
C.
representation
chosen
Indicates that one entity stands in for, symbolizes, or depicts another entity in some context.
-
D.
resents
Indicates that one entity feels bitterness, anger, or lingering ill will toward another, typically due to a perceived wrong or unfair treatment.
-
E.
greenRepresents
Indicates that one entity uses the color green to symbolize, denote, or stand for another entity or concept.
- 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_69aed937fa8881908208ef3801060826 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee634c6ac819099653c660c286746 |
completed | March 9, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69aee3d3c92c819081d9d5c45ef37a5d |
completed | March 9, 2026, 3:14 p.m. |
Created at: March 9, 2026, 3:13 p.m.