Triple
T8862528
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wettin-Löbejün |
E210926
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Rothenburg
Rothenburg is a locality within the town of Wettin-Löbejün in the German state of Saxony-Anhalt.
|
E768934
|
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: Rothenburg | Statement: [Wettin-Löbejün, hasPart, Rothenburg]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rothenburg Context triple: [Wettin-Löbejün, hasPart, Rothenburg]
-
A.
Rothenburg ob der Tauber
Rothenburg ob der Tauber is a well-preserved medieval town in Bavaria, Germany, famed for its intact city walls, half-timbered houses, and picturesque old town.
-
B.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
C.
Würzburg
Würzburg is a historic city in southern Germany known for its baroque architecture, the Würzburg Residence palace, and its location along the Main River in the Franconia wine region.
-
D.
Gräfenhausen
Gräfenhausen is a district of the town of Weiterstadt in the state of Hesse, Germany.
-
E.
Schweinfurt
Schweinfurt is a city in northern Bavaria, Germany, historically known for its ball bearing industry and as a strategic target during World War II.
- 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: Rothenburg Triple: [Wettin-Löbejün, hasPart, Rothenburg]
Generated description
Rothenburg is a locality within the town of Wettin-Löbejün in the German state of Saxony-Anhalt.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Rothenburg Target entity description: Rothenburg is a locality within the town of Wettin-Löbejün in the German state of Saxony-Anhalt.
-
A.
Rothenburg ob der Tauber
Rothenburg ob der Tauber is a well-preserved medieval town in Bavaria, Germany, famed for its intact city walls, half-timbered houses, and picturesque old town.
-
B.
Günzburg
Günzburg is a small Bavarian town in southern Germany, historically notable as the birthplace of Nazi physician Josef Mengele.
-
C.
Würzburg
Würzburg is a historic city in southern Germany known for its baroque architecture, the Würzburg Residence palace, and its location along the Main River in the Franconia wine region.
-
D.
Gräfenhausen
Gräfenhausen is a district of the town of Weiterstadt in the state of Hesse, Germany.
-
E.
Schweinfurt
Schweinfurt is a city in northern Bavaria, Germany, historically known for its ball bearing industry and as a strategic target during World War II.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc610263048190931bb2c3ac573a08 |
completed | April 1, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cfc929fb94819091980b0994b4f02d |
completed | April 3, 2026, 2:05 p.m. |
| NEDg | Description generation | batch_69cfca00ffa08190ad66fb99572a6275 |
completed | April 3, 2026, 2:09 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cfca84937881909707497d733218e5 |
completed | April 3, 2026, 2:11 p.m. |
Created at: March 30, 2026, 6:50 p.m.