Triple
T18708786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umhausen |
E457443
|
entity |
| Predicate | hasSubdivision |
P747
|
FINISHED |
| Object | Umhausen village |
—
|
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: Umhausen village | Statement: [Umhausen, hasSubdivision, Umhausen village]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Umhausen village Context triple: [Umhausen, hasSubdivision, Umhausen village]
-
A.
Hildrizhausen
Hildrizhausen is a small municipality in the German state of Baden-Württemberg, situated near the Schönbuch forest southwest of Stuttgart.
-
B.
Umhausen
chosen
Umhausen is a municipality in the Tyrolean Alps of western Austria, known for its scenic mountain setting and proximity to popular hiking and skiing areas.
-
C.
Haimhausen
Haimhausen is a small municipality in Upper Bavaria, Germany, known for its historic castle and rural setting north of Munich.
-
D.
Eilshausen
Eilshausen is a village and district within the municipality of Hiddenhausen in North Rhine-Westphalia, Germany.
-
E.
Mickhausen
Mickhausen is a small municipality in the Swabian region of Bavaria in southern 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_69d8d392aad081909fe31aa03e6e97d1 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56719383481909d68c9e873ca0800 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 10, 2026, 11:50 a.m.