Triple
T17131792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronnie |
E415735
|
entity |
| Predicate | hasVariantSpelling |
P457
|
FINISHED |
| Object | Ronny |
E789887
|
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: Ronny | Statement: [Ronnie, hasVariantSpelling, Ronny]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronny Context triple: [Ronnie, hasVariantSpelling, Ronny]
-
A.
Ronny
chosen
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.
-
B.
Ronny J
Ronny J is an American record producer and rapper known for his hard-hitting, distorted trap beats and work with prominent hip-hop artists like Denzel Curry, XXXTentacion, and Kanye West.
-
C.
Ronnie
Ronnie is the central protagonist of the crime thriller film "Catch .44," around whom the movie’s violent, twisting plot revolves.
-
D.
Ronnie
Ronnie is a masculine given name commonly used in English-speaking countries, often as a diminutive of Ronald or Veronica.
-
E.
Roni
"Roni" is a 1988 R&B single by Bobby Brown, known for its smooth new jack swing style and romantic lyrics.
- 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_69d886d15af4819092f92f8a129763e6 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3f02a9fbc81909d820d29417aa55c |
completed | April 18, 2026, 8:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01414eca3c8190aeec22fab3b5e767 |
completed | May 11, 2026, 2:39 a.m. |
Created at: April 10, 2026, 5:36 a.m.