Triple
T3915151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | France (on behalf of French overseas departments in the Caribbean) |
E88817
|
entity |
| Predicate | representedEntityType |
P16833
|
FINISHED |
| Object | overseas departments |
—
|
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: overseas departments | Statement: [France (on behalf of French overseas departments in the Caribbean), representedEntityType, overseas departments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: representedEntityType Context triple: [France (on behalf of French overseas departments in the Caribbean), representedEntityType, overseas departments]
-
A.
documentedEntityType
chosen
Indicates that an entity has been documented as belonging to a specific type or category.
-
B.
representationType
Indicates the specific form or mode in which something is represented or expressed (e.g., as a symbol, image, model, or description).
-
C.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
D.
representedFrom
Indicates that one entity serves as a representation or depiction of another entity.
-
E.
oreType
Indicates the specific kind or classification of ore associated with 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_69aed955229881909e85e73ffab1d343 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef188b474819087680db42b04ecdd |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee75eedcc81908088ff4dbb8be56b |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:22 p.m.