Triple
T8688700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Expo Porte de Versailles |
E206230
|
entity |
| Predicate | hasTotalExhibitionArea |
P9481
|
FINISHED |
| Object | approximately 228000 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: approximately 228000 square metres | Statement: [Paris Expo Porte de Versailles, hasTotalExhibitionArea, approximately 228000 square metres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTotalExhibitionArea Context triple: [Paris Expo Porte de Versailles, hasTotalExhibitionArea, approximately 228000 square metres]
-
A.
hasExhibitionArea
chosen
Indicates that an entity includes or provides a designated space or area for exhibitions or displays.
-
B.
hasAreaTotal
Indicates the total surface area associated with an entity, typically measured over its entire extent.
-
C.
hasFloorArea
Indicates that an entity possesses a specified amount of floor space as a measurable area.
-
D.
coveredArea
Indicates that one entity occupies or extends over a specific spatial region or surface area associated with another entity.
-
E.
hasCirculationArea
Indicates that an entity includes or is associated with a designated circulation space or area used for movement or flow (e.g., of people, materials, or vehicles).
- 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.