Triple
T909764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Werner Heisenberg |
E19631
|
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 Heisenberg, givenName, Werner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Werner Context triple: [Werner Heisenberg, givenName, Werner]
-
A.
Werner
chosen
Werner is a given name and surname of Germanic origin, commonly used in German-speaking countries.
-
B.
Helmut
Helmut is a masculine given name of German origin, historically common in German-speaking countries.
-
C.
Ernst
Ernst is a masculine given name of Germanic origin, commonly used in German-speaking and Scandinavian countries.
-
D.
Kurt Student
Kurt Student was a German Luftwaffe general and pioneer of airborne forces who played a key role in developing and leading Nazi Germany’s paratrooper units during World War II.
-
E.
Hermann
Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b2dca5208190bc9f17cd9dd6a98f |
completed | March 1, 2026, 9:42 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad013923908190b20e11e14df7fa14 |
completed | March 8, 2026, 4:55 a.m. |
Created at: March 1, 2026, 7:39 p.m.