Triple
T15064429
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werner Wittmann |
E379717
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Werner |
E151920
|
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: Werner | Statement: [Werner Wittmann, givenName, Werner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werner Context triple: [Werner Wittmann, givenName, Werner]
-
A.
Werner
chosen
Werner is a given name and surname of Germanic origin, commonly used in German-speaking countries.
-
B.
Felix Krull
Felix Krull is the charming, quick-witted con artist and social climber who narrates Thomas Mann’s picaresque novel "The Confessions of Felix Krull."
-
C.
Günther
Günther is the zoologist who first formally described the impressed tortoise species Manouria impressa.
-
D.
Günther
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
E.
Helmut
Helmut is a masculine given name of German origin, historically common in German-speaking countries.
- 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee803ac81908bb7d66e49c2eb72 |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feae0fd7dc8190a10c8eb7542c3088 |
completed | May 9, 2026, 3:46 a.m. |
Created at: April 10, 2026, 3:02 a.m.