Triple
T14863477
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baumgarten |
E349558
|
entity |
| Predicate | locatedInAdministrativeEntity |
P40
|
FINISHED |
| Object | Penzing |
E821846
|
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: Penzing | Statement: [Baumgarten, locatedInAdministrativeEntity, Penzing]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Penzing Context triple: [Baumgarten, locatedInAdministrativeEntity, Penzing]
-
A.
Penzing
chosen
Penzing is a district in the western part of Vienna, Austria, known for its residential areas, green spaces, and proximity to the Vienna Woods.
-
B.
Patersdorf
Patersdorf is a small municipality in the Bavarian Forest region of southeastern Germany.
-
C.
Neuötting
Neuötting is a small Bavarian town in southeastern Germany known for its historic town center and location near the Austrian border.
-
D.
Pasching
Pasching is a small municipality in Upper Austria, near Linz, known for its shopping centers and the Waldstadion football stadium.
-
E.
Gmunden
Gmunden is a picturesque town in Upper Austria known for its lakeside setting on the Traunsee and its historic ceramics industry.
- 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_69d822ed7e1881909b90fca143ad7e34 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69ded574d0ec8190a6afed672ba6c2f9 |
completed | April 15, 2026, 12:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe72a87dd88190b0f0c3b9b625a7e6 |
completed | May 8, 2026, 11:32 p.m. |
Created at: April 10, 2026, 1:54 a.m.