Triple
T7455773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doesburg |
E172118
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Gelderland |
E14197
|
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: Gelderland | Statement: [Doesburg, locatedIn, Gelderland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gelderland Context triple: [Doesburg, locatedIn, Gelderland]
-
A.
Gelderland
chosen
Gelderland is a large province in the eastern Netherlands known for its varied landscapes, including the forested Veluwe region and the river areas along the Rhine, Waal, and IJssel.
-
B.
Zuid-Holland
Zuid-Holland is a densely populated coastal province in the western Netherlands that includes major cities such as Rotterdam and The Hague.
-
C.
North Brabant
North Brabant is a southern province of the Netherlands known for its historic cities, Catholic cultural heritage, and role as a key battleground during World War II.
-
D.
Central Netherlands
Central Netherlands is a geographic region in the heart of the Netherlands that includes the city of Utrecht and serves as an important hub for commerce, transportation, and culture.
-
E.
Overijssel
Overijssel is a province in the eastern Netherlands known for its historic Hanseatic cities, rivers, and varied landscapes of forests, heathlands, and farmland.
- 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_69c68a66554c8190add75c65942c0317 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3af58dc819093fb0482482779a3 |
completed | March 27, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8681d57c08190b72d1b010db3a065 |
completed | March 28, 2026, 11:45 p.m. |
Created at: March 27, 2026, 3:15 p.m.