Triple
T14407519
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ronda Rousey |
E357237
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Ronda Jean Rousey |
E357237
|
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: Ronda Jean Rousey | Statement: [Ronda Rousey, fullName, Ronda Jean Rousey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ronda Jean Rousey Context triple: [Ronda Rousey, fullName, Ronda Jean Rousey]
-
A.
Ronda Rousey
chosen
Ronda Rousey is an American professional wrestler, former mixed martial arts champion, and Olympic judoka who gained fame in the UFC before becoming a top star in WWE.
-
B.
Gina Carano
Gina Carano is an American actress and former mixed martial artist best known for her roles in action films and the Star Wars series "The Mandalorian."
-
C.
Carlos Condit
Carlos Condit is an American mixed martial artist and former UFC Interim Welterweight Champion known for his aggressive striking and finishing ability.
-
D.
Amanda Nunes
Amanda Nunes is a Brazilian mixed martial artist widely regarded as one of the greatest female fighters in UFC history, known for holding titles in multiple weight classes.
-
E.
Yazmin Newell
Yazmin Newell is an actress known for her role in the science-fiction television series "Moonhaven."
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90c7a068819081b4b516983a1412 |
completed | April 14, 2026, 7:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd7a38003c819083f276fcaae52da9 |
completed | May 8, 2026, 5:52 a.m. |
Created at: April 10, 2026, 1:17 a.m.