Triple
T16381247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soest district |
E397811
|
entity |
| Predicate | containsAdministrativeTerritorialEntity |
P747
|
FINISHED |
| Object | Ense |
E990688
|
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: Ense | Statement: [Soest district, containsAdministrativeTerritorialEntity, Ense]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ense Context triple: [Soest district, containsAdministrativeTerritorialEntity, Ense]
-
A.
Ense
chosen
Ense is a municipality in the Soest district of North Rhine-Westphalia, Germany, situated along the Möhne River and known for its rural character and historic villages.
-
B.
Ennesi
Ennesi are the inhabitants or natives of the city of Enna in central Sicily, Italy.
-
C.
Eanske
Eanske is the local dialect name for the Dutch city of Enschede, commonly used in the regional Twents language.
-
D.
Essa
Essa is a rural township in Simcoe County, Ontario, Canada, known for its agricultural landscape and proximity to the city of Barrie.
-
E.
Ennery
Ennery is a commune in the Val-d'Oise department in northern France, situated near Pontoise in the Île-de-France region.
- 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_69d87f2880b48190ae1a9673a3bbef80 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e319dd0e0c8190812bde6a2f7d9644 |
completed | April 18, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0035689ef08190ba980a359498ca56 |
completed | May 10, 2026, 7:36 a.m. |
Created at: April 10, 2026, 5:08 a.m.