Triple
T3525924
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drava |
E74537
|
entity |
| Predicate | flowsThroughCity |
P10456
|
FINISHED |
| Object |
Lienz
Lienz is a small alpine town in East Tyrol, Austria, known for its picturesque mountain scenery and role as a regional cultural and economic center.
|
E366732
|
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: Lienz | Statement: [Drava, flowsThroughCity, Lienz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lienz Context triple: [Drava, flowsThroughCity, Lienz]
-
A.
Landeck
Landeck is a small town in the Tyrolean Alps of western Austria, known as a regional transport hub and gateway to nearby ski and hiking areas.
-
B.
Kufstein
Kufstein is a historic town in the Austrian state of Tyrol, known for its medieval fortress and picturesque setting in the Alps near the German border.
-
C.
Oberwart
Oberwart is a town in eastern Austria known as a regional center with a significant Hungarian-speaking minority and a mix of industrial, commercial, and cultural activities.
-
D.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
E.
Schärding
Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
- 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: Lienz Triple: [Drava, flowsThroughCity, Lienz]
Generated description
Lienz is a small alpine town in East Tyrol, Austria, known for its picturesque mountain scenery and role as a regional cultural and economic center.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lienz Target entity description: Lienz is a small alpine town in East Tyrol, Austria, known for its picturesque mountain scenery and role as a regional cultural and economic center.
-
A.
Landeck
Landeck is a small town in the Tyrolean Alps of western Austria, known as a regional transport hub and gateway to nearby ski and hiking areas.
-
B.
Kufstein
Kufstein is a historic town in the Austrian state of Tyrol, known for its medieval fortress and picturesque setting in the Alps near the German border.
-
C.
Oberwart
Oberwart is a town in eastern Austria known as a regional center with a significant Hungarian-speaking minority and a mix of industrial, commercial, and cultural activities.
-
D.
Vöcklabruck
Vöcklabruck is a small historic town in Upper Austria known as a regional center near the Attersee lake and the foothills of the Alps.
-
E.
Schärding
Schärding is a historic Austrian town on the border with Germany, known for its well-preserved baroque old town and riverside setting.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6a8d0c819094d38b9c47fb67b4 |
completed | March 8, 2026, 6:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b38bca41a88190b5550b9c1e763092 |
completed | March 13, 2026, 4 a.m. |
| NEDg | Description generation | batch_69b38c3c0b508190be86d75a6ec3a6a4 |
completed | March 13, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b38c939c948190a137d79030d9c8d1 |
completed | March 13, 2026, 4:03 a.m. |
Created at: March 8, 2026, 3:19 p.m.