Triple
T26321273
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | coat of arms of Saint Barthélemy |
E662116
|
entity |
| Predicate | partOfHeraldryOf |
P183699
|
FINISHED |
| Object | France |
—
|
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: France | Statement: [coat of arms of Saint Barthélemy, partOfHeraldryOf, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfHeraldryOf Context triple: [coat of arms of Saint Barthélemy, partOfHeraldryOf, France]
-
A.
regionOfHeraldry
Indicates a relationship where a heraldic symbol, coat of arms, or emblem is associated with or belongs to a specific geographic or administrative region.
-
B.
heraldicCharge
Indicates that one entity serves as a heraldic charge, i.e., a symbolic figure or emblem placed on another entity’s coat of arms or shield.
-
C.
coatOfArms
Indicates that one entity serves as the heraldic emblem or coat of arms representing another entity.
-
D.
heraldicAspect
Indicates a relationship where one entity serves as a heraldic feature, attribute, or component in the coat of arms or heraldic representation of another entity.
-
E.
coatOfArmsFeatures
Indicates that a coat of arms includes or displays specific symbols, colors, or design elements as part of its heraldic composition.
- 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_69ee812e73048190aae587f1d51e5a06 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f7a283388c81908e4a9ee3369e8d6f |
completed | May 3, 2026, 7:31 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
| PDg | Predicate description generation | batch_69f7a224365081908ff6958e3b30bd05 |
completed | May 3, 2026, 7:29 p.m. |
Created at: April 26, 2026, 10:28 p.m.