Triple
T16461495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bailey |
E399816
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Bayley |
E600020
|
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: Bayley | Statement: [Bailey, hasVariant, Bayley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bayley Context triple: [Bailey, hasVariant, Bayley]
-
A.
Bayley
chosen
Bayley is a prominent American professional wrestler best known for her successful career in WWE, where she has held multiple women’s championships and evolved from a beloved fan-favorite to a top villain.
-
B.
Bayley
Bayley is a surname most prominently associated with Stephen Bayley, a British design critic, author, and cultural commentator.
-
C.
Bailee
Bailee is the first name of American actress Bailee Madison, known for her roles in films like "Bridge to Terabithia" and the TV series "Good Witch."
-
D.
Riley
Riley is a given name commonly used for people of any gender in English-speaking countries.
-
E.
Riley
Riley is a historic British automobile marque best known for its sporting and luxury cars produced during the early to mid-20th century.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32d819d548190bc76a0ec2e223437 |
completed | April 18, 2026, 7:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f555f6081908b1f0d524b6fb9a7 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:10 a.m.