Triple
T15621734
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sneek |
E375572
|
entity |
| Predicate | connectedByRailTo |
P848
|
FINISHED |
| Object | Stavoren |
E420290
|
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: Stavoren | Statement: [Sneek, connectedByRailTo, Stavoren]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stavoren Context triple: [Sneek, connectedByRailTo, Stavoren]
-
A.
Stavoren
chosen
Stavoren is a historic Frisian port city in the Netherlands, known as one of the traditional Eleven Cities and for its maritime heritage on the IJsselmeer.
-
B.
Pipervika
Pipervika is a bay and surrounding neighborhood in central Oslo, Norway, situated between the City Hall and the Aker Brygge waterfront district.
-
C.
Bregava
Bregava is a river in Bosnia and Herzegovina known for flowing through the town of Stolac before joining the Neretva River.
-
D.
Sulden
Sulden is a small alpine village and ski resort in South Tyrol, northern Italy, known for its dramatic high-mountain scenery in the Ortler Alps.
-
E.
Vodnjese
Vodnjese is a local dialect of the Istriot language traditionally spoken in and around the town of Vodnjan in Istria.
- 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_69d85ccf2794819096cda4cbcb02d478 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04e9a95f08190b0013ba1428849d3 |
completed | April 16, 2026, 2:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f3da754819085a6bd9876b12c65 |
completed | May 9, 2026, 4:22 p.m. |
Created at: April 10, 2026, 4:13 a.m.