Triple
T13504028
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Martinair |
E320964
|
entity |
| Predicate | founder |
P104
|
FINISHED |
| Object | Martin Schröder |
E320964
|
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: Martin Schröder | Statement: [Martinair, founder, Martin Schröder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Martin Schröder Context triple: [Martinair, founder, Martin Schröder]
-
A.
Martin Schröder
chosen
Martin Schröder is a Dutch aviation entrepreneur best known as the founder of the charter airline Martinair.
-
B.
Peter Lohmeyer
Peter Lohmeyer is a German actor known for his versatile performances in film, television, and theater, often appearing in prominent German productions since the late 1980s.
-
C.
Christian Scholz
Christian Scholz is a German computer scientist and open-source developer known for his contributions to web technologies and social software.
-
D.
Olli Dittrich
Olli Dittrich is a German actor, comedian, and musician best known for his work in television sketch comedy and film.
-
E.
Florian Haertel
Florian Haertel is a German journalist and photographer best known as the former husband of British actress Alex Kingston.
- 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_69d807629d6c8190998f1b9bb12d2ed0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbaf810e248190a060481004503f96 |
completed | April 12, 2026, 2:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcdeea935081909baffaadc8a8fac7 |
completed | May 7, 2026, 6:50 p.m. |
Created at: April 9, 2026, 9:43 p.m.