Triple
T22110629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TUM Weihenstephan campus |
E546405
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Freising |
—
|
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: Freising | Statement: [TUM Weihenstephan campus, locatedIn, Freising]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Freising Context triple: [TUM Weihenstephan campus, 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.
Traunstein
Traunstein is a prominent limestone mountain in the Salzkammergut region of Upper Austria, overlooking Lake Traunsee and popular for hiking and climbing.
-
D.
Kaufbeuren
Kaufbeuren is a historic Bavarian town in southern Germany known for its well-preserved medieval old town and traditional Swabian culture.
-
E.
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.
- 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_69e11e378dc08190896d6a51597afd5a |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f12948c2ec819083340787b2062649 |
completed | April 28, 2026, 9:40 p.m. |
Created at: April 16, 2026, 8:30 p.m.