Triple
T17085785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Labidus |
E414592
|
entity |
| Predicate | describedBy |
P264
|
FINISHED |
| Object | Julius Roger |
E1232168
|
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: Julius Roger | Statement: [Labidus, describedBy, Julius Roger]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julius Roger Context triple: [Labidus, describedBy, Julius Roger]
-
A.
Julius Roger
chosen
Julius Roger was a 19th-century German physician and entomologist known for his taxonomic work describing numerous insect species.
-
B.
Julius Tennon
Julius Tennon is an American actor and film producer known for his work in television and film and for co-founding JuVee Productions with his wife, Viola Davis.
-
C.
Julius May
Julius May is a pseudonym used by American science fiction and fantasy author Julian May.
-
D.
Julius Francis
Julius Francis was a prominent Buffalo, New York civic leader and philanthropist known for his efforts to establish and promote the city’s Pan-American Exposition of 1901.
-
E.
Julius Jenkins
Julius Jenkins is an American professional basketball player best known as a prolific scoring guard in European leagues, particularly in Germany's Basketball Bundesliga.
- 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_69d886cef44c8190ba56c44b4e863e64 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3dbe6d5288190bdaec41c642d52a2 |
completed | April 18, 2026, 7:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a012ee651ec8190a37c5997f394d24b |
completed | May 11, 2026, 1:20 a.m. |
Created at: April 10, 2026, 5:35 a.m.