Triple
T4263006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Don Schlitz |
E96147
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Donald |
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: Donald | Statement: [Don Schlitz, givenName, Donald]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donald Context triple: [Don Schlitz, givenName, Donald]
-
A.
Donald
Donald is the given name of Don Revie, the renowned English football player and manager best known for his successful tenure at Leeds United.
-
B.
Donald
Donald is the given name of Donald Trump, the 45th president of the United States and a prominent businessman and media personality.
-
C.
Donald
Donald III of Scotland was a late 11th-century King of Scots who briefly ruled following the death of his brother Malcolm III.
-
D.
Don
chosen
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
E.
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.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34fc821ec8190a7204aaf89d24a6b |
completed | March 12, 2026, 11:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5b78ffbf881909d59faae665abd36 |
completed | March 14, 2026, 7:31 p.m. |
Created at: March 12, 2026, 11:06 p.m.