Triple
T4858413
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zillertal |
E108593
|
entity |
| Predicate | river |
P165
|
FINISHED |
| Object | Ziller |
E206836
|
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: Ziller | Statement: [Zillertal, river, Ziller]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ziller Context triple: [Zillertal, river, Ziller]
-
A.
Ziller
chosen
The Ziller is a river in the Austrian state of Tyrol that flows through the Zillertal valley before joining the Inn River.
-
B.
Tuiskon Ziller
Tuiskon Ziller was a 19th-century German philosopher and educator known for developing and systematizing Herbartian pedagogy, significantly shaping modern educational theory.
-
C.
Piper Skih
Piper Skih is a musician best known for having been a member of the American alternative rock band Blue October.
-
D.
Bode Miller
Bode Miller is an American alpine ski racer and multiple Olympic and World Championship medalist known for his aggressive, risk-taking style on the slopes.
-
E.
Ted Ligety
Ted Ligety is an American alpine ski racer renowned for his dominance in giant slalom, including multiple Olympic and World Championship gold medals.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d5b2f008190a5fd11d3aec165fb |
completed | March 20, 2026, 3:52 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be5cf05d7c8190ac6e1b9e93b5256f |
completed | March 21, 2026, 8:55 a.m. |
Created at: March 20, 2026, 1:26 p.m.