Triple
T16712621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erik Spoelstra |
E406144
|
entity |
| Predicate | playedFor |
P2170
|
FINISHED |
| Object | TuS Herten |
E406144
|
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: TuS Herten | Statement: [Erik Spoelstra, playedFor, TuS Herten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TuS Herten Context triple: [Erik Spoelstra, playedFor, TuS Herten]
-
A.
TuS Herten
chosen
TuS Herten is a German basketball club where future NBA coach Erik Spoelstra played professionally early in his career.
-
B.
Hammersborg
Hammersborg is a central neighborhood in Oslo, Norway, known for housing key government buildings and cultural institutions.
-
C.
Randers FC
Randers FC is a professional Danish football club based in the city of Randers that competes in the Danish Superliga.
-
D.
Herning Fremad
Herning Fremad was a Danish football club from Herning that later became part of the foundation for the professional club FC Midtjylland.
-
E.
Vejle Boldklub
Vejle Boldklub is a Danish professional football club known for its historic success in the national league and cup competitions.
- 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_69d8838f242881908abd8bc138795886 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e386530d9c8190b91ec3aac7dc2518 |
completed | April 18, 2026, 1:25 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0091a95180819099abd50dd153e229 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 5:20 a.m.