Triple
T10540754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wallhausen |
E248687
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Wallhausen@en |
E248687
|
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: Wallhausen@en | Statement: [Wallhausen, hasNameInLanguage, Wallhausen@en]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wallhausen@en Context triple: [Wallhausen, hasNameInLanguage, Wallhausen@en]
-
A.
Wallhausen
chosen
Wallhausen is a village in present-day Saxony-Anhalt, Germany, historically notable as the birthplace of Otto I, Holy Roman Emperor.
-
B.
Wienhausen
Wienhausen is a historic village in Lower Saxony, Germany, best known for its medieval Cistercian nunnery and well-preserved half-timbered architecture.
-
C.
Haase
Haase is a surname of German origin commonly borne by individuals in German-speaking countries and their descendants.
-
D.
Hausen
Hausen is a small suburban district of the town of Herbrechtingen in the state of Baden-Württemberg, Germany.
-
E.
Hausen
Hausen is a small municipality in the district of Kelheim in the German state of Bavaria.
- 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_69d381c733c08190ab1dd6239f5f34ae |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d50a582be48190856c6f272eea4dcf |
completed | April 7, 2026, 1:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d9341d96c08190a6ba644b9acfe2c8 |
completed | April 10, 2026, 5:32 p.m. |
Created at: April 6, 2026, 12:32 p.m.