Triple
T6133672
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WU Campus |
E136779
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Messe Wien |
E571413
|
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: Messe Wien | Statement: [WU Campus, locatedNear, Messe Wien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Messe Wien Context triple: [WU Campus, locatedNear, Messe Wien]
-
A.
Messe Berlin
Messe Berlin is a major exhibition and trade fair center in Berlin, Germany, hosting international trade shows, conferences, and large-scale events.
-
B.
Messe Düsseldorf
Messe Düsseldorf is a major international trade fair and exhibition center in Düsseldorf, Germany, hosting numerous global industry events and conventions.
-
C.
Messe Wien Exhibition & Congress Center
chosen
Messe Wien Exhibition & Congress Center is a major modern trade fair and convention venue in Vienna, Austria, hosting international exhibitions, conferences, and large-scale events.
-
D.
Berliner Messe
Berliner Messe is a minimalist sacred choral composition by Estonian composer Arvo Pärt, written in his signature tintinnabuli style for the Latin Mass.
-
E.
Nürnberg Messe
Nürnberg Messe is one of Germany’s largest international trade fair and exhibition centers, hosting numerous global industry events and conferences in Nuremberg.
- 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05c7f34d081909e589b201b22be21 |
completed | March 22, 2026, 9:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c1416e8fa8819092bf830cbaa56647 |
completed | March 23, 2026, 1:34 p.m. |
Created at: March 22, 2026, 4:15 p.m.