Triple
T2680128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French overseas territories |
E56552
|
entity |
| Predicate | haveDiverseStatusDefinedBy |
P42196
|
FINISHED |
| Object | French domestic 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: French domestic law | Statement: [French overseas territories, haveDiverseStatusDefinedBy, French domestic law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveDiverseStatusDefinedBy Context triple: [French overseas territories, haveDiverseStatusDefinedBy, French domestic law]
-
A.
supportsDiversity
Indicates that one entity actively promotes, encourages, or upholds diversity in or for another entity.
-
B.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
C.
hasNationalStatus
Indicates that an entity possesses an official national-level designation, recognition, or status within a country.
-
D.
diversifiedIn
Indicates that an entity has expanded its involvement, investments, or activities across multiple different areas, sectors, or asset types.
-
E.
hasStatusLabel
Indicates that an entity is associated with a specific status expressed as a human-readable label.
- 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_69ab4a4b13fc81909dfdb3f23da46832 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abda2f7bf88190a1e3103dd014d871 |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd81ab9d08190b72b6104c6dbc769 |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abda2dc5788190b4b83cb9ed08266c |
completed | March 7, 2026, 7:56 a.m. |
Created at: March 6, 2026, 9:54 p.m.