Triple
T15497498
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austrian Alps |
E378855
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Schladming |
E726350
|
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: Schladming | Statement: [Austrian Alps, contains, Schladming]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Schladming Context triple: [Austrian Alps, contains, Schladming]
-
A.
Schladming
chosen
Schladming is a renowned Austrian alpine ski resort town in Styria, famous for hosting major international ski races and World Cup events.
-
B.
Oberstdorf
Oberstdorf is a renowned alpine resort town in southern Germany known for skiing, ski jumping, and hiking amid dramatic mountain scenery.
-
C.
Kitzbühel
Kitzbühel is a renowned Austrian alpine town famous for its ski resorts and the annual Hahnenkamm downhill race.
-
D.
Igls
Igls is an Austrian alpine village near Innsbruck known for its winter sports facilities and role in hosting Olympic events.
-
E.
Zell am See
Zell am See is a popular Austrian alpine town and lakeside resort known for its scenic mountain setting, skiing, and outdoor recreation.
- 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_69d85cd53a7c819080f5b9042c4c199e |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03fb0aee081909db1c54349ec8492 |
completed | April 16, 2026, 1:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffb0319f248190a37c9afa09c32428 |
completed | May 9, 2026, 10:07 p.m. |
Created at: April 10, 2026, 3:53 a.m.