Triple
T12351013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SV Straelen |
E294484
|
entity |
| Predicate | homeTown |
P5864
|
FINISHED |
| Object | Straelen |
E956038
|
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: Straelen | Statement: [SV Straelen, homeTown, Straelen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Straelen Context triple: [SV Straelen, homeTown, Straelen]
-
A.
Straelen
chosen
Straelen is a historic town in western Germany’s Lower Rhine region, known for its agricultural economy and proximity to the Dutch border.
-
B.
Steggerda
Steggerda is a small village in the municipality of Weststellingwerf in the province of Friesland in the northern Netherlands.
-
C.
Steenokkerzeel
Steenokkerzeel is a municipality in the Belgian province of Flemish Brabant, known for its proximity to Brussels and its location near major transport infrastructure.
-
D.
Tessenderlo
Tessenderlo is a municipality in the Belgian province of Limburg, known for its chemical industry and location near the Albert Canal.
-
E.
Aalst
Aalst is a historic city in the Belgian province of East Flanders, known for its textile industry and famous annual carnival.
- 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_69d6ab6ccbec8190b09e2d357aa80064 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f7cbff08190849cd2aec4ce3243 |
completed | April 10, 2026, 6:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f655608a0c81908002f9d79d017ded |
completed | May 2, 2026, 7:49 p.m. |
Created at: April 8, 2026, 9:53 p.m.