Triple
T21206265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barbeya |
E522590
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object | William Barbey |
—
|
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: William Barbey | Statement: [Barbeya, namedAfter, William Barbey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: William Barbey Context triple: [Barbeya, namedAfter, William Barbey]
-
A.
William Barbey
chosen
William Barbey was a Swiss botanist known for his contributions to plant taxonomy and for having the plant genus Barbeya named in his honor.
-
B.
Charles DeKay
Charles DeKay was an American poet, art critic, and cultural promoter active in the late 19th and early 20th centuries.
-
C.
William Demarest
William Demarest was an American character actor best known for his roles in numerous Hollywood films and the television series "My Three Sons."
-
D.
William Hornbeck
William Hornbeck was an influential American film editor known for his work on numerous classic Hollywood films and for helping to shape modern editing techniques.
-
E.
Philip DeGuere
Philip DeGuere was an American television producer, writer, and director best known for his work on popular series in the 1970s and 1980s.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73435322c8190bf4156fbd14edc5c |
completed | April 21, 2026, 8:24 a.m. |
Created at: April 16, 2026, 3:20 p.m.