Triple
T10159157
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guglielmo |
E233843
|
entity |
| Predicate | etymologicallyRelatedTo |
P5801
|
FINISHED |
| Object | Wilhelm |
E52726
|
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: Wilhelm | Statement: [Guglielmo, etymologicallyRelatedTo, Wilhelm]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wilhelm Context triple: [Guglielmo, etymologicallyRelatedTo, Wilhelm]
-
A.
Wilhelm
chosen
Wilhelm is a Germanic given name, equivalent to William, historically borne by numerous European nobles, rulers, and notable figures.
-
B.
Gerhard
Gerhard is a masculine given name of German origin, historically common in German-speaking countries.
-
C.
Gustav
Gustav is a masculine given name of German origin, borne by several notable historical figures including scientists, artists, and royalty.
-
D.
Hermann
Hermann Minkowski was a German mathematician best known for developing the geometric formulation of special relativity using four-dimensional spacetime.
-
E.
Hermann
Hermann is a French publishing house best known for issuing influential mathematical works, including the foundational texts of the Bourbaki school.
- 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_69ca848e80748190b91d1e04d35512c7 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cdec56d944819081bc6ea36c905ba2 |
completed | April 2, 2026, 4:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6a7d465bc8190b419de253616b0fd |
completed | April 8, 2026, 7:09 p.m. |
Created at: March 30, 2026, 9:09 p.m.