Triple
T6870084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Carlos Buell |
E158518
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Don |
E75078
|
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: Don | Statement: [Don Carlos Buell, givenName, Don]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Don Context triple: [Don Carlos Buell, givenName, Don]
-
A.
Don
The Don is a major river in southwestern Russia that flows from the Central Russian Upland to the Sea of Azov, historically serving as an important trade route and cultural boundary.
-
B.
Don
chosen
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
C.
Danny
Danny is a masculine given name, often used as a diminutive of Daniel.
-
D.
Danny
Danny is the young boy protagonist of the science-fiction adventure film "Zathura: A Space Adventure," whose discovery of a mysterious board game launches the story’s intergalactic journey.
-
E.
Danny
Danny is a supporting character in Woody Allen's 2013 drama film "Blue Jasmine," involved in the personal and emotional turmoil surrounding the protagonist's life.
- 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_69c68831e3648190a643c328122e4d43 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d8aa47f48190bc7cad3cc652f530 |
completed | March 27, 2026, 7:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c742a114008190be431f1e10d94501 |
completed | March 28, 2026, 2:53 a.m. |
Created at: March 27, 2026, 2:22 p.m.