Triple
T10071891
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Voorne-Putten |
E213647
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Abbenbroek |
E227871
|
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: Abbenbroek | Statement: [Voorne-Putten, hasTown, Abbenbroek]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Abbenbroek Context triple: [Voorne-Putten, hasTown, Abbenbroek]
-
A.
Abbenbroek
chosen
Abbenbroek is a small village in the Dutch province of South Holland, known for its rural character and historic church.
-
B.
Nieuwendijk
Nieuwendijk is one of Amsterdam’s oldest and busiest shopping streets, running through the historic city center near Dam Square.
-
C.
Groesbeek
Groesbeek is a village in the Dutch province of Gelderland, known for its hilly landscape, World War II history, and wine production.
-
D.
Bullewijk
Bullewijk is a small waterway and urban canal in Amsterdam’s southeastern area, integrated into the city’s network of rivers and canals.
-
E.
Schipbeek
Schipbeek is a small river in the eastern Netherlands that flows through the provinces of Overijssel and Gelderland before joining the IJssel.
- 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_69d29aaa61308190b134b49a6c1c1131 |
completed | April 5, 2026, 5:23 p.m. |
Created at: March 30, 2026, 8:59 p.m.