Triple
T14054122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seminary in Freising |
E338167
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Freising |
E375515
|
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: Freising | Statement: [Seminary in Freising, locatedIn, Freising]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freising Context triple: [Seminary in Freising, locatedIn, Freising]
-
A.
Freising
chosen
Freising is a historic Bavarian town near Munich, known for its cathedral hill and one of the world’s oldest operating breweries at Weihenstephan.
-
B.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
C.
Kaufbeuren
Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
-
D.
Füssen
Füssen is a picturesque Bavarian town in southern Germany, known for its historic old town, proximity to Neuschwanstein Castle, and scenic location near the Alps.
-
E.
Eichstätt
Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
- 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_69d81c67ba6c819091935650dfb3b895 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c8bc54c8190a12f0fc056568538 |
completed | April 14, 2026, 1:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f1f80648190a4a0e8260ac95194 |
completed | May 9, 2026, 4:21 p.m. |
Created at: April 9, 2026, 10:20 p.m.