Triple
T6560717
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Krimpenerwaard |
E152574
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object | Vlist |
E600257
|
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: Vlist | Statement: [Krimpenerwaard, containsSettlement, Vlist]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vlist Context triple: [Krimpenerwaard, containsSettlement, Vlist]
-
A.
Vlist
chosen
Vlist was a former municipality in the Dutch province of South Holland that later became part of the larger municipality of Krimpenerwaard.
-
B.
Lister
Lister is a surname most famously associated with Joseph Lister, the pioneering British surgeon who introduced antiseptic techniques to modern medicine.
-
C.
litas
The litas was the national currency of Lithuania before the adoption of the euro.
-
D.
VSL
VSL is the station code for Venezia Santa Lucia, the main railway terminal serving the historic center of Venice, Italy.
-
E.
LisaList
LisaList is a list management and data structure utility component of the Lisa OS environment, used for organizing and manipulating collections of items within the system.
- 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_69c688058d6881908c19b309cc55dbfa |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6ae37a5b0819091692fc5def270b9 |
completed | March 27, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6d55c817481908f570b85a6b407f9 |
completed | March 27, 2026, 7:07 p.m. |
Created at: March 27, 2026, 1:52 p.m.