Triple
T10071889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voorne-Putten |
E213647
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Geervliet |
E233210
|
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: Geervliet | Statement: [Voorne-Putten, hasTown, Geervliet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Geervliet Context triple: [Voorne-Putten, hasTown, Geervliet]
-
A.
Geervliet
chosen
Geervliet is a small historic town in the western Netherlands, located in the province of South Holland.
-
B.
Schipbeek
Schipbeek is a small river in the eastern Netherlands that flows through the provinces of Overijssel and Gelderland before joining the IJssel.
-
C.
Gogeldrie
Gogeldrie is a small rural locality in the Riverina region of New South Wales, Australia, known for its agricultural surroundings and proximity to the Murrumbidgee River.
-
D.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
-
E.
Strandvliet
Strandvliet is a metro station in Amsterdam that serves passengers on the city's rapid transit network.
- 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_69ca839add308190b57d53b4ec21f2d0 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd01279388190b94c8def00425c78 |
completed | April 2, 2026, 2:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d2b63d13fc8190bdeac3c7b2529052 |
completed | April 5, 2026, 7:21 p.m. |
Created at: March 30, 2026, 8:59 p.m.