Triple
T12041819
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tachov |
E286678
|
entity |
| Predicate | hasTwinTown |
P919
|
FINISHED |
| Object |
Waldmünchen
Waldmünchen is a small town in the Bavarian Forest region of southeastern Germany, near the Czech border, known for its scenic surroundings and cross-border cultural ties.
|
E1021695
|
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: Waldmünchen | Statement: [Tachov, hasTwinTown, Waldmünchen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Waldmünchen Context triple: [Tachov, hasTwinTown, Waldmünchen]
-
A.
Schwabmünchen
Schwabmünchen is a small Bavarian town in southern Germany known for its historic center and location near the city of Augsburg.
-
B.
Maroldsweisach
Maroldsweisach is a municipality in the Haßberge district of northern Bavaria, Germany, known for its rural setting and historic Franconian character.
-
C.
Wunsiedel
Wunsiedel is a historic town in northeastern Bavaria, Germany, known for its location in the Fichtel Mountains and its traditional Franconian architecture.
-
D.
Schöngeising
Schöngeising is a small municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
-
E.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
- 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: Waldmünchen Triple: [Tachov, hasTwinTown, Waldmünchen]
Generated description
Waldmünchen is a small town in the Bavarian Forest region of southeastern Germany, near the Czech border, known for its scenic surroundings and cross-border cultural ties.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Waldmünchen Target entity description: Waldmünchen is a small town in the Bavarian Forest region of southeastern Germany, near the Czech border, known for its scenic surroundings and cross-border cultural ties.
-
A.
Schwabmünchen
Schwabmünchen is a small Bavarian town in southern Germany known for its historic center and location near the city of Augsburg.
-
B.
Maroldsweisach
Maroldsweisach is a municipality in the Haßberge district of northern Bavaria, Germany, known for its rural setting and historic Franconian character.
-
C.
Wunsiedel
Wunsiedel is a historic town in northeastern Bavaria, Germany, known for its location in the Fichtel Mountains and its traditional Franconian architecture.
-
D.
Schöngeising
Schöngeising is a small municipality in Upper Bavaria, Germany, known for its rural character and proximity to the city of Munich.
-
E.
Taufkirchen
Taufkirchen is a municipality in Bavaria, Germany, known for its strong aerospace and defense industry presence.
- 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_69d6ab4780948190bdb9f7620c2ac27e |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9040d13108190bd1a969fa62aae5a |
completed | April 10, 2026, 2:07 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6e2548a848190a3a72415a5e4d0fd |
completed | May 3, 2026, 5:51 a.m. |
| NEDg | Description generation | batch_69f6e32bf5508190b4dc58971f8f64d0 |
completed | May 3, 2026, 5:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69f6e40a13c8819084daf9b77b46a181 |
completed | May 3, 2026, 5:58 a.m. |
Created at: April 8, 2026, 9:47 p.m.