Triple
T34538454
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Army |
E886734
|
entity |
| Predicate | usedUniformsOf |
P46425
|
FINISHED |
| Object | French Army |
—
|
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: French Army | Statement: [Blue Army, usedUniformsOf, French Army]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedUniformsOf Context triple: [Blue Army, usedUniformsOf, French Army]
-
A.
usesUniform
Indicates that one entity regularly wears or employs a standardized set of clothing or equipment designated as a uniform.
-
B.
usedUniformColor
chosen
Indicates that multiple entities share or employed the same uniform color in a given context.
-
C.
isUniform
Indicates that all elements or parts within a given set, structure, or context share the same characteristics or value.
-
D.
areUniform
Indicates that all elements in a given set or collection share the same value, property, or characteristic.
-
E.
includesUniformType
Indicates that one entity contains or encompasses a specific type of uniform within its scope or composition.
- 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_69f349ce5eb881909e431c670944aa68 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71ff03438819095c5c377f2bcae9d |
completed | May 3, 2026, 10:14 a.m. |
| PD | Predicate disambiguation | batch_69f71cc8074c81909ae09bea2acf1a09 |
completed | May 3, 2026, 10 a.m. |
Created at: May 1, 2026, 2:02 a.m.