Triple
T15205354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gmunden |
E363373
|
entity |
| Predicate | nearMountain |
P31783
|
FINISHED |
| Object |
Traunstein
Traunstein is a prominent limestone mountain in the Salzkammergut region of Upper Austria, overlooking Lake Traunsee and popular for hiking and climbing.
|
E1242220
|
NE FINISHED |
How this triple was built (4 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: Traunstein | Statement: [Gmunden, nearMountain, Traunstein]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Traunstein Context triple: [Gmunden, nearMountain, Traunstein]
-
A.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
B.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
C.
Eichstätt
Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
-
D.
Straßkirchen
Straßkirchen is a municipality in Lower Bavaria, Germany, known for its rural character and location near the city of Straubing.
-
E.
Kempten
Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Traunstein Triple: [Gmunden, nearMountain, Traunstein]
Generated description
Traunstein is a prominent limestone mountain in the Salzkammergut region of Upper Austria, overlooking Lake Traunsee and popular for hiking and climbing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Traunstein Target entity description: Traunstein is a prominent limestone mountain in the Salzkammergut region of Upper Austria, overlooking Lake Traunsee and popular for hiking and climbing.
-
A.
Traunstein
Traunstein is a town in southeastern Bavaria, Germany, known as a regional administrative and cultural center near the Chiemsee and the Alps.
-
B.
Rosenheim
Rosenheim is a town in Upper Bavaria, Germany, known as a regional economic and transportation hub near the Alps.
-
C.
Eichstätt
Eichstätt is a historic Bavarian town in southern Germany known for its baroque architecture, Catholic university, and location within the Altmühltal Nature Park.
-
D.
Straßkirchen
Straßkirchen is a municipality in Lower Bavaria, Germany, known for its rural character and location near the city of Straubing.
-
E.
Kempten
Kempten is a historic town in Bavaria, Germany, considered one of the country’s oldest urban settlements and known for its location in the Allgäu region.
- F. None of above. chosen
Provenance (5 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b7964c8190bc8dc3444b94f15e |
completed | April 15, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfb725d48190bdca0a85ca7f440c |
completed | May 10, 2026, 6:34 p.m. |
| NEDg | Description generation | batch_6a00d1a88c188190bde3fe3c01efb453 |
completed | May 10, 2026, 6:42 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d20ae52c8190b4c45af68aa40399 |
completed | May 10, 2026, 6:44 p.m. |
Created at: April 10, 2026, 3:11 a.m.