Triple
T20729942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freudenstadt (district) |
E509545
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Egenhausen |
—
|
NE NERFINISHED |
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: Egenhausen | Statement: [Freudenstadt (district), hasMunicipality, Egenhausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Egenhausen Context triple: [Freudenstadt (district), hasMunicipality, Egenhausen]
-
A.
Egenhausen
chosen
Egenhausen is a small municipality in southwestern Germany, known for its rural setting and surrounding natural landscapes.
-
B.
Leutershausen
Leutershausen is a historic small town in Bavaria, Germany, known for its well-preserved medieval character and traditional Franconian architecture.
-
C.
Nattenhausen
Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
-
D.
Balzhausen
Balzhausen is a small municipality in the Bavarian region of Swabia in southern Germany.
-
E.
Eilshausen
Eilshausen is a village and district within the municipality of Hiddenhausen in North Rhine-Westphalia, Germany.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4c589c08190834fb5d86d0efa2b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c1ec9820819093a07f90503686b2 |
completed | April 21, 2026, 12:16 a.m. |
Created at: April 16, 2026, 12:30 p.m.