Triple
T10998996
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | R. Walter Cunningham |
E259957
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ronnie |
E415735
|
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: Ronnie | Statement: [R. Walter Cunningham, givenName, Ronnie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronnie Context triple: [R. Walter Cunningham, givenName, Ronnie]
-
A.
Ronnie
chosen
Ronnie is a masculine given name commonly used in English-speaking countries, often as a diminutive of Ronald or Veronica.
-
B.
Ronny
Ronny is a Malaysian-born comedian and actor best known as a correspondent on The Daily Show and for creating and starring in the sitcom Ronny Chieng: International Student.
-
C.
Ronnie Fish
Ronnie Fish is a recurring comic character in P. G. Wodehouse’s Blandings Castle stories, known as Lord Emsworth’s mischievous and often romantically entangled nephew.
-
D.
Randy
Randy is the nickname of Randy Moffitt, a former Major League Baseball relief pitcher best known for his long tenure with the San Francisco Giants in the 1970s.
-
E.
Randy
Randy is a supporting character in the dark comedy film "The Opposite of Sex," involved in the tangled romantic and emotional conflicts that drive the story.
- 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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d796d3b08c81909376cd73c42fcefe |
completed | April 9, 2026, 12:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e34530ada081909dc58ff0261e93e7 |
completed | April 18, 2026, 8:47 a.m. |
Created at: April 8, 2026, 9:25 p.m.