Triple
T24913850
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Nord Villepinte |
E623922
|
entity |
| Predicate | indoorExhibitionArea |
P9481
|
FINISHED |
| Object | about 198000 square metres |
—
|
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: about 198000 square metres | Statement: [Paris Nord Villepinte, indoorExhibitionArea, about 198000 square metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: indoorExhibitionArea Context triple: [Paris Nord Villepinte, indoorExhibitionArea, about 198000 square metres]
-
A.
exhibitionSpaceType
Indicates the specific kind or category of space used to display or present exhibitions.
-
B.
hasExhibitionArea
chosen
Indicates that an entity includes or provides a designated space or area for exhibitions or displays.
-
C.
fieldOfExhibition
Indicates the domain or area in which something is publicly presented, displayed, or exhibited.
-
D.
hasIndoorExhibits
Indicates that an entity provides or contains exhibits that are located indoors.
-
E.
exhibitionUse
Indicates that something is used, intended, or designated for display in an exhibition or exhibit context.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f4238ab92081908c5c8f807b2f1816 |
completed | May 1, 2026, 3:52 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:28 a.m.