Triple
T20986366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raphael Semmes |
E516900
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Semmes |
—
|
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: Semmes | Statement: [Raphael Semmes, familyName, Semmes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Semmes Context triple: [Raphael Semmes, familyName, Semmes]
-
A.
Semmes
chosen
Semmes is a surname most notably associated with Raphael Semmes, a Confederate naval officer and captain of the commerce raider CSS Alabama during the American Civil War.
-
B.
Semo
Semo is an ancient Roman deity associated with oaths, loyalty, and sacred trust, often identified with the god Sancus.
-
C.
Ließem
Ließem is a village-level district within the municipality of Wachtberg in the Rhein-Sieg-Kreis region of North Rhine-Westphalia, Germany.
-
D.
Gombauld
Gombauld is a modernist painter and one of the central, satirically portrayed guests at the country-house gathering in Aldous Huxley’s novel "Crome Yellow."
-
E.
Sulien
Sulien is a Welsh saint traditionally venerated as a local holy figure associated with churches in Wales.
- 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_69e0b4ffac148190bbade9f0eceb660b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6fbe31cec8190a1007414148b8abe |
completed | April 21, 2026, 4:24 a.m. |
Created at: April 16, 2026, 1:49 p.m.