Triple
T22550063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lebern electoral district |
E557534
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Messen |
—
|
NE NERFINISHED |
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: Messen | Statement: [Lebern electoral district, hasMunicipality, Messen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Messen Context triple: [Lebern electoral district, hasMunicipality, Messen]
-
A.
Messen
chosen
Messen is a municipality in the canton of Solothurn in Switzerland, known for its rural character and location in the Bucheggberg region.
-
B.
Messe
Messe is a Nuremberg U-Bahn station serving the city’s exhibition and trade fair grounds.
-
C.
Toki Messe
Toki Messe is a large convention and exhibition center in Niigata, Japan, known for hosting major events, trade shows, and cultural festivals.
-
D.
The Expo
The Expo is a well-known multipurpose event and exhibition venue in Portland, Oregon, hosting trade shows, conventions, and community 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 (2 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_69e11e59db848190b4272ecd2b690ffd |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15f74512c8190b5369e19a4bc6325 |
completed | April 29, 2026, 1:31 a.m. |
Created at: April 16, 2026, 8:52 p.m.