Triple
T9487347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Semmering Pass |
E228793
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Mürzzuschlag |
E474492
|
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: Mürzzuschlag | Statement: [Semmering Pass, near, Mürzzuschlag]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mürzzuschlag Context triple: [Semmering Pass, near, Mürzzuschlag]
-
A.
Mürzzuschlag
chosen
Mürzzuschlag is a small Austrian town in the state of Styria, known historically for its iron industry and as a winter sports and railway hub in the Eastern Alps.
-
B.
Mürz
Mürz is a river in southeastern Austria that flows through the state of Styria and is an important tributary of the Mur River.
-
C.
Schönbichl
Schönbichl is a small island located in the Eibsee, a picturesque alpine lake at the foot of Germany’s Zugspitze mountain.
-
D.
Bad Salzungen
Bad Salzungen is a spa town in Thuringia, Germany, known for its saline springs and therapeutic health resorts.
-
E.
Leißling
Leißling is a small municipality in the Weißenfels area of Saxony-Anhalt, Germany, known for its local industry and residential character.
- 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_69ca847424f081908180305555139f7a |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd80c443b88190968d2092a73e1ee4 |
completed | April 1, 2026, 8:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d12d18fd908190b562fa0a8dad7c63 |
completed | April 4, 2026, 3:24 p.m. |
Created at: March 30, 2026, 7:55 p.m.