Triple
T10307105
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Forchheim district |
E241792
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Hausen |
E808431
|
NE FINISHED |
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: Hausen | Statement: [Forchheim district, containsTown, Hausen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hausen Context triple: [Forchheim district, containsTown, Hausen]
-
A.
Hausen
Hausen is a small suburban district of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
B.
Hausen
chosen
Hausen is a small municipality in the district of Kelheim in the German state of Bavaria.
-
C.
Nattenhausen
Nattenhausen is a small village in the Bavarian district of Günzburg in southern Germany.
-
D.
Wienhausen
Wienhausen is a historic village in Lower Saxony, Germany, best known for its medieval Cistercian nunnery and well-preserved half-timbered architecture.
-
E.
Warthausen
Warthausen is a small municipality in the district of Biberach in the German state of Baden-Württemberg, known for its historic castle and rural setting.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381ac38808190a8ca7457c85b625b |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d30a6c888190acdd0a645247736a |
completed | April 7, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d71d60be1481909dc1330f150e3897 |
completed | April 9, 2026, 3:30 a.m. |
Created at: April 6, 2026, 11:46 a.m.