Triple
T4088306
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Twente |
E87641
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Salland |
E128791
|
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: Salland | Statement: [Twente, borders, Salland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Salland Context triple: [Twente, borders, Salland]
-
A.
Salland
chosen
Salland is a historical and rural region in the Dutch province of Overijssel, known for its scenic landscapes, small towns, and agricultural character.
-
B.
Vechta
Vechta is a town in Lower Saxony, Germany, known for its historical significance, university, and annual Stoppelmarkt fair.
-
C.
Sappemeer
Sappemeer is a town in the province of Groningen in the northeastern Netherlands, historically known for its peat colonies and waterways.
-
D.
Flevoland
Flevoland is the youngest Dutch province, largely created through land reclamation from the IJsselmeer in the central Netherlands.
-
E.
Drenthe
Drenthe is a rural province in the northeastern Netherlands known for its prehistoric dolmens, heathlands, and forests.
- 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_69aed94425148190be337845d56fac22 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefca899008190b5ada98bdb79639f |
completed | March 9, 2026, 5 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5d04bc33c819082cf79f4445610f1 |
completed | March 14, 2026, 9:16 p.m. |
Created at: March 9, 2026, 3:39 p.m.