Triple
T22587459
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JGU Mainz |
E564837
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | Uni Mainz |
—
|
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: Uni Mainz | Statement: [JGU Mainz, shortName, Uni Mainz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uni Mainz Context triple: [JGU Mainz, shortName, Uni Mainz]
-
A.
JGU Mainz
chosen
JGU Mainz is a major public research university located in Mainz, Germany, named after printing pioneer Johannes Gutenberg.
-
B.
Mainz 05
Mainz 05 is a German professional football club based in Mainz, best known for competing in the Bundesliga and having a passionate fan culture.
-
C.
FSV Mainz 05
FSV Mainz 05 is a German professional football club based in Mainz, best known for competing in the Bundesliga.
-
D.
FH Münster
FH Münster is a German university of applied sciences based in Münster, known for its practice-oriented programs and strong links to industry and regional development.
-
E.
Frankfurt U2
Frankfurt U2 is a line of the Frankfurt U-Bahn rapid transit system that connects central Frankfurt with its northern suburbs.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1615de7d48190b1ca46c76a1e609c |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 2:46 p.m.