Triple
T3753383
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Wirth |
E81385
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Wirth |
E168959
|
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: Wirth | Statement: [Christian Wirth, familyName, Wirth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wirth Context triple: [Christian Wirth, familyName, Wirth]
-
A.
Wirth
chosen
Wirth is a Swiss surname most notably associated with computer scientist Niklaus Wirth, the designer of several influential programming languages.
-
B.
Wüthrich
Wüthrich is a Swiss surname most notably associated with Nobel Prize–winning chemist Kurt Wüthrich.
-
C.
Worner
Worner is a surname and variant spelling of "Warner," used by various individuals and families, particularly in English-speaking countries.
-
D.
Weinert
Weinert is a German-language surname borne by various notable individuals in fields such as the arts, sciences, and public life.
-
E.
Wisser
The Wisser is a river in Germany that serves as a right-bank tributary of the Sieg.
- 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_69ad8b19b7b08190a6188804e99c53e9 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adcb9340e0819083215989718b4598 |
completed | March 8, 2026, 7:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4e5044f3c8190969828966b37e729 |
completed | March 14, 2026, 4:33 a.m. |
Created at: March 8, 2026, 3:35 p.m.