Triple
T27315115
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montreuil |
E689317
|
entity |
| Predicate | isPartOfFunctionalArea |
P184585
|
FINISHED |
| Object | aire d’attraction de Paris |
—
|
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: aire d’attraction de Paris | Statement: [Montreuil, isPartOfFunctionalArea, aire d’attraction de Paris]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isPartOfFunctionalArea Context triple: [Montreuil, isPartOfFunctionalArea, aire d’attraction de Paris]
-
A.
isPartOfBusinessArea
Indicates that one entity belongs to, is included within, or falls under the scope of a particular business area.
-
B.
isPartOfPolicyArea
Indicates that one policy, topic, or issue belongs to, falls under, or is categorized within a broader policy area or domain.
-
C.
isOneOfMainAreasFor
Indicates that something belongs to the primary set of domains, topics, or fields associated with another entity.
-
D.
partOfProgramArea
Indicates that one entity functions as a sub-area or component within a broader program area.
-
E.
isGrowthAreaFor
Indicates that a particular domain, skill, or area represents an opportunity or target for development or improvement for an entity.
- 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_69ef355c53a08190a8a92e355a7ce115 |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f7b365288c8190bcb11fcfba028737 |
completed | May 3, 2026, 8:43 p.m. |
| PD | Predicate disambiguation | batch_69f7b1b8a9fc8190a1279e67a2d12707 |
completed | May 3, 2026, 8:36 p.m. |
| PDg | Predicate description generation | batch_69f7b2f2b9ac8190aa05b8a1aa18ec2d |
completed | May 3, 2026, 8:41 p.m. |
Created at: April 27, 2026, 11:30 a.m.