Triple
T15698811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joost Lips |
E380537
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Overijse |
E241178
|
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: Overijse | Statement: [Joost Lips, birthPlace, Overijse]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Overijse Context triple: [Joost Lips, birthPlace, Overijse]
-
A.
Overijse
chosen
Overijse is a municipality in the Flemish Brabant province of Belgium, known for its green residential character and extensive vineyards.
-
B.
Waalre
Waalre is a municipality and village in the southern Netherlands, located in the province of North Brabant near the city of Eindhoven.
-
C.
Geervliet
Geervliet is a small historic town in the western Netherlands, located in the province of South Holland.
-
D.
Betuwe
Betuwe is a fertile riverine region in the Dutch province of Gelderland, renowned for its extensive fruit orchards and scenic landscapes between the Rhine and Waal rivers.
-
E.
Bollenstreek
Bollenstreek is a coastal region in the western Netherlands famous for its extensive flower bulb fields and springtime tulip displays.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f6d71308190971c10c599da9645 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff7571f1888190b83af75ec9c7432b |
completed | May 9, 2026, 5:57 p.m. |
Created at: April 10, 2026, 4:44 a.m.