Triple
T3814404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Herman Boerhaave |
E84216
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Voorhout |
E690991
|
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: Voorhout | Statement: [Herman Boerhaave, placeOfBirth, Voorhout]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Voorhout Context triple: [Herman Boerhaave, placeOfBirth, Voorhout]
-
A.
Voorhout
chosen
Voorhout is a village in South Holland, Netherlands, that forms part of the municipality of Teylingen.
-
B.
Houten
Houten is a Dutch town in the province of Utrecht, known for its bicycle-friendly urban design and as the home of the Royal Dutch Mint.
-
C.
Barendrecht
Barendrecht is a suburban town in the western Netherlands, located just south of Rotterdam and known for its residential character and logistics industry.
-
D.
Oosterhout
Oosterhout is a town and municipality in the southern Netherlands known for its historic monasteries and proximity to the city of Breda.
-
E.
Noordwijkerhout
Noordwijkerhout is a town in South Holland, Netherlands, known for its bulb flower fields and role in the Dutch "Dune and Bulb 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_69aed931f5908190be2c07af66d4df25 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aee8de9e948190bf461e55ad00eddb |
completed | March 9, 2026, 3:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09b0002948190bb9d47cd0c766003 |
completed | April 4, 2026, 5 a.m. |
Created at: March 9, 2026, 3:17 p.m.