Triple
T2963179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haarlem |
E80096
|
entity |
| Predicate | locatedOnRiver |
P165
|
FINISHED |
| Object | Spaarne |
E240514
|
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: Spaarne | Statement: [Haarlem, locatedOnRiver, Spaarne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Spaarne Context triple: [Haarlem, locatedOnRiver, Spaarne]
-
A.
Spaarne
chosen
Spaarne is a river in the province of North Holland in the Netherlands that flows through the historic city of Haarlem.
-
B.
Overijse
Overijse is a municipality in the Flemish Brabant province of Belgium, known for its green residential character and extensive vineyards.
-
C.
Geervliet
Geervliet is a small historic town in the western Netherlands, located in the province of South Holland.
-
D.
Uithoorn
Uithoorn is a town and municipality in the province of North Holland in the Netherlands, situated along the Amstel River.
-
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_69ad8b1341848190bd19dbf46892887d |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9957602c819089b673966fd619e0 |
completed | March 8, 2026, 3:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b12e229afc8190ae634dbfb3ac4313 |
completed | March 11, 2026, 8:56 a.m. |
Created at: March 8, 2026, 2:57 p.m.