Triple
T8688706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paris Expo Porte de Versailles |
E206230
|
entity |
| Predicate | hasConferenceCentre |
P15338
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Paris Expo Porte de Versailles, hasConferenceCentre, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConferenceCentre Context triple: [Paris Expo Porte de Versailles, hasConferenceCentre, yes]
-
A.
hasConferenceSpace
chosen
Indicates that an entity provides or includes dedicated space suitable for holding conferences, meetings, or similar gatherings.
-
B.
hasCulturalCentre
Indicates that one entity possesses, hosts, or contains a cultural centre associated with it.
-
C.
hasCircuitCentre
Indicates that an entity has, is associated with, or is organized around a specific circuit center that serves as its focal or central point.
-
D.
venueComplex
Indicates that one venue is a complex or larger facility that contains or encompasses another venue.
-
E.
hasTradeFairCenter
Indicates that a place or organization possesses or hosts a dedicated trade fair center where exhibitions or trade fairs are held.
- 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.