Triple
T29589269
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | French territorial reform of 2014 |
E754107
|
entity |
| Predicate | affectedUnit |
P1586
|
FINISHED |
| Object | Alsace region |
—
|
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: Alsace region | Statement: [French territorial reform of 2014, affectedUnit, Alsace region]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedUnit Context triple: [French territorial reform of 2014, affectedUnit, Alsace region]
-
A.
affectedEntity
Indicates that an entity is the one that is impacted, influenced, or acted upon as a result of an event, action, or process.
-
B.
affectedAsset
Indicates that an entity has an impact on, or causes a change to, a particular asset.
-
C.
affectedArea
chosen
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
D.
affectedClass
Indicates that one entity (typically a change, event, or issue) has an impact on or is relevant to a particular class or category of items.
-
E.
affectedCompany
Indicates that a company is impacted or influenced by a particular event, action, or 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_69f0ef836ac88190bd809dc58b5ec907 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f6d6a6b04c8190bee4cf9c00665ef7 |
completed | May 3, 2026, 5:01 a.m. |
| PD | Predicate disambiguation | batch_69f6d26ceb08819091c71c001e954936 |
completed | May 3, 2026, 4:43 a.m. |
Created at: April 28, 2026, 6:13 p.m.