Triple
T6718078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronnie Fish |
E153322
|
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: [Ronnie Fish, givenName, Ronnie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronnie Context triple: [Ronnie Fish, 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.
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.
-
C.
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.
-
D.
Ronnie Knox
Ronnie Knox was an American football quarterback active in the 1950s, known for his college career at UCLA and California and a brief stint in the NFL and CFL.
-
E.
Lonnie
Lonnie is the given first name of American country music singer and songwriter Mel Tillis.
- 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_69c68809b4608190a2509ddb5ab87f05 |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d12765a48190b485176dc2ffa0fa |
completed | March 27, 2026, 6:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7009b9b64819095ae1a65cd72c374 |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:07 p.m.