Triple
T8688701
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Expo Porte de Versailles |
E206230
|
entity |
| Predicate | hasIndoorExhibitionArea |
P9481
|
FINISHED |
| Object | over 200000 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: over 200000 square metres | Statement: [Paris Expo Porte de Versailles, hasIndoorExhibitionArea, over 200000 square metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndoorExhibitionArea Context triple: [Paris Expo Porte de Versailles, hasIndoorExhibitionArea, over 200000 square metres]
-
A.
hasIndoorExhibits
Indicates that an entity provides or contains exhibits that are located indoors.
-
B.
hasExhibitionArea
chosen
Indicates that an entity includes or provides a designated space or area for exhibitions or displays.
-
C.
hasIndoorArea
Indicates that an entity possesses or includes an area or space that is located indoors or within a building.
-
D.
hasOutdoorExhibits
Indicates that a place or institution includes exhibits or displays located in outdoor or open-air areas.
-
E.
hasExhibits
Indicates that an entity (such as a museum, gallery, or event) displays or presents certain items, artworks, or objects as part of its collection or show.
- 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_69ca835481fc819084e33d3bc883bfa6 |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc57334b0c8190903a5a1784e74791 |
completed | March 31, 2026, 11:22 p.m. |
| PD | Predicate disambiguation | batch_69cc4569f9048190b9c86b4c81103d35 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:33 p.m.