Triple
T23258226
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gerhard Weinberg |
E581930
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Gerhard |
—
|
NE NERFINISHED |
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: Gerhard | Statement: [Gerhard Weinberg, givenName, Gerhard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gerhard Context triple: [Gerhard Weinberg, givenName, Gerhard]
-
A.
Gerhard
chosen
Gerhard is a masculine given name of German origin, historically common in German-speaking countries.
-
B.
Wilhelm
Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
-
C.
Lothar
Lothar is a masculine given name of Germanic origin, historically borne by various European nobles, military figures, and notable individuals.
-
D.
Hartmut
Hartmut is a masculine German given name, most notably borne by Nobel Prize–winning biochemist Hartmut Michel.
-
E.
Hans-Karl
Hans-Karl is the given name of Hans-Karl Freiherr von Esebeck, a German Wehrmacht general during World War II.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c710c48190aff03d210642a043 |
completed | April 29, 2026, 5:19 a.m. |
Created at: April 17, 2026, 4:11 p.m.