Triple
T9498775
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tirschenreuth (district) |
E229080
|
entity |
| Predicate | hasCapital |
P204
|
FINISHED |
| Object | Tirschenreuth |
E268424
|
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: Tirschenreuth | Statement: [Tirschenreuth (district), hasCapital, Tirschenreuth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tirschenreuth Context triple: [Tirschenreuth (district), hasCapital, Tirschenreuth]
-
A.
Tirschenreuth
chosen
Tirschenreuth is a town in northeastern Bavaria, Germany, known for its historic town center and surrounding lake and pond landscapes.
-
B.
Schneizlreuth
Schneizlreuth is a small Bavarian municipality in southeastern Germany, known for its alpine landscapes and location near the Austrian border.
-
C.
Kreuth
Kreuth is a Bavarian municipality in southern Germany, known for its alpine landscape and location near Lake Tegernsee in the Bavarian Alps.
-
D.
Schwarzach
Schwarzach is a municipality in the Austrian state of Vorarlberg, located in the district of Bregenz.
-
E.
Dinkelsbühl
Dinkelsbühl is a well-preserved medieval town in Bavaria, Germany, renowned for its intact city walls, historic half-timbered houses, and picturesque old town.
- 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_69ca84753660819098e8d416e89e26ae |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd983a94c48190a7ddf95a953c4ecc |
completed | April 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9330fa33c8190b507ad18362a6c64 |
completed | April 10, 2026, 5:27 p.m. |
Created at: March 30, 2026, 7:56 p.m.