Triple
T18421683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helge Schneider |
E442037
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Helge |
—
|
NE NERFINISHED |
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: Helge | Statement: [Helge Schneider, givenName, Helge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helge Context triple: [Helge Schneider, givenName, Helge]
-
A.
Helge
chosen
Helge is a given name, used in various European countries, that is closely related to the name Helga.
-
B.
Halvard
Halvard is a masculine given name of Scandinavian origin, particularly common in Norway.
-
C.
Holger
Holger is a masculine given name of Scandinavian origin, commonly used in countries such as Sweden and Denmark.
-
D.
Hjølmo
Hjølmo is a small rural area in the municipality of Eidfjord in Vestland county, Norway, known for its scenic fjord and mountain surroundings.
-
E.
Torbjørn
Torbjørn is a Scandinavian masculine given name, particularly common in Norway, derived from Old Norse elements meaning "Thor" and "bear."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9eb8a508190a942fd75ebd8b1dc |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e51a2be6bc8190b2812f77ff4cc960 |
completed | April 19, 2026, 6:08 p.m. |
Created at: April 10, 2026, 10:47 a.m.