Triple
T16994924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2005 Geneva Motor Show |
E412289
|
entity |
| Predicate | venue |
P373
|
FINISHED |
| Object | Palexpo |
E1099423
|
NE 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: Palexpo | Statement: [2005 Geneva Motor Show, venue, Palexpo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Palexpo Context triple: [2005 Geneva Motor Show, venue, Palexpo]
-
A.
Palexpo
chosen
Palexpo is a large convention and exhibition center in Geneva, Switzerland, known for hosting major international events such as the Geneva International Motor Show.
-
B.
Helexpo
Helexpo is Greece’s national exhibition and conference organizer, best known for staging major trade fairs and events such as the Thessaloniki International Fair.
-
C.
Crocus Expo
Crocus Expo is one of Russia’s largest and most modern exhibition and convention centers, located in Moscow’s Krasnogorsk district and hosting major trade shows, conferences, and events.
-
D.
Resch Expo
Resch Expo is a modern exhibition and convention center located in Ashwaubenon, Wisconsin, hosting trade shows, conferences, and large public events.
-
E.
Expo
Expo is an open-source platform and toolchain for building, deploying, and iterating on React Native applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d285f35881908c32b2f27ba7f0ac |
completed | April 18, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00dc16fbdc819095411a056b9942c3 |
completed | May 10, 2026, 7:27 p.m. |
Created at: April 10, 2026, 5:32 a.m.