Triple
T1348071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hermann Ebbinghaus |
E28816
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hermann |
E24628
|
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: Hermann | Statement: [Hermann Ebbinghaus, givenName, Hermann]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hermann Context triple: [Hermann Ebbinghaus, givenName, Hermann]
-
A.
Hermann
chosen
Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
-
B.
Günther
Günther is a German masculine given name traditionally associated with figures of Germanic origin and culture.
-
C.
Wilhelm
Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
-
D.
Helmut
Helmut is a masculine given name of German origin, historically common in German-speaking countries.
-
E.
Heinrici
Heinrici is a German surname most notably associated with Gotthard Heinrici, a senior Wehrmacht general during World War II.
- 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_69a498571d248190a0ac9eb02d97097f |
completed | March 1, 2026, 7:49 p.m. |
| NER | Named-entity recognition | batch_69a4c2418e38819094683d6e1efc6e56 |
completed | March 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adfb8a58ec81908b2bb5c27283bafa |
completed | March 8, 2026, 10:43 p.m. |
Created at: March 1, 2026, 7:56 p.m.