Triple
T14262412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | N211 |
E353554
|
entity |
| Predicate | connects |
P390
|
FINISHED |
| Object | Wateringen |
E205642
|
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: Wateringen | Statement: [N211, connects, Wateringen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wateringen Context triple: [N211, connects, Wateringen]
-
A.
Wateringen
chosen
Wateringen is a town in the western Netherlands that forms part of the municipality of Westland in the province of South Holland.
-
B.
Meerssen
Meerssen is a historic town and municipality in the Dutch province of Limburg, known for its medieval basilica and scenic location near Maastricht.
-
C.
Valkenswaard
Valkenswaard is a town in the southern Netherlands known for its strong equestrian culture and international show jumping events.
-
D.
Woensdrecht
Woensdrecht is a municipality in the Dutch province of North Brabant, known for its strategic location near the Belgian border and its military air base.
-
E.
Esens
Esens is a small historic town in Lower Saxony, Germany, known for its coastal North Sea location and traditional East Frisian character.
- 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_69d8278c43e08190824146f4632b89a5 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de63563fc88190b0abdbf8529c65eb |
completed | April 14, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd647b37a8819095fe0bb62e0373fb |
completed | May 8, 2026, 4:20 a.m. |
Created at: April 10, 2026, 1:09 a.m.