Triple
T15736539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fort Vijfhuizen |
E381486
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Vijfhuizen |
E78033
|
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: Vijfhuizen | Statement: [Fort Vijfhuizen, locatedIn, Vijfhuizen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vijfhuizen Context triple: [Fort Vijfhuizen, locatedIn, Vijfhuizen]
-
A.
Vijfhuizen
chosen
Vijfhuizen is a village in the Dutch province of North Holland, situated within the municipality of Haarlemmermeer near Haarlem.
-
B.
Zevenhuizen
Zevenhuizen is a village in the Dutch province of South Holland, known for its rural character and proximity to the city of Rotterdam.
-
C.
Zevenhuizen
Zevenhuizen is a village in the Dutch province of Groningen, located within the municipality of Westerkwartier.
-
D.
Oldenzaal
Oldenzaal is a historic city in the eastern Netherlands known for its medieval center and location near the German border in the province of Overijssel.
-
E.
Hornhuizen
Hornhuizen is a small village in the province of Groningen in the northern Netherlands, known for its rural landscape and historic church.
- 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_69d86d9cdb648190bf3171be0bd7d872 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04fd6eb888190b7a9b07b76e62c0d |
completed | April 16, 2026, 2:56 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffeb7c2a6081908e957d39ec056062 |
completed | May 10, 2026, 2:20 a.m. |
Created at: April 10, 2026, 4:46 a.m.