Triple
T1862404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmut Hasse |
E34844
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Helmut |
E76767
|
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: Helmut | Statement: [Helmut Hasse, givenName, Helmut]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Helmut Context triple: [Helmut Hasse, givenName, Helmut]
-
A.
Helmut
chosen
Helmut is a masculine given name of German origin, historically common in German-speaking countries.
-
B.
Erich
Erich is a masculine given name of German origin, commonly used in German-speaking countries and beyond.
-
C.
Hermann
Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
-
D.
Hermann
Hermann is a German surname borne by various notable individuals across fields such as philosophy, science, and the arts.
-
E.
Erich Roland
Erich Roland is a cinematographer known for his work on the documentary film "He Named Me Malala."
- 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb09e714881909cef0f7e77b5b3b9 |
completed | March 7, 2026, 4:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2b4b974081908da05bc63f923215 |
completed | March 9, 2026, 8:19 p.m. |
Created at: March 4, 2026, 7:34 p.m.