Triple
T18034825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Richard Kiley |
E431480
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Kiley |
—
|
NE NERFINISHED |
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: Kiley | Statement: [Richard Kiley, familyName, Kiley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kiley Context triple: [Richard Kiley, familyName, Kiley]
-
A.
Kiley
chosen
Kiley is a given name used for people of any gender, often considered a variant spelling of names like Kylie or Kylee.
-
B.
Kayely
Kayely is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
-
C.
Kelsey
Kelsey is a given name most famously associated with American actor and comedian Kelsey Grammer.
-
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 (2 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_69d8b9050fb48190890155145deb0a66 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4be38766c8190ae95701f4575469c |
completed | April 19, 2026, 11:36 a.m. |
Created at: April 10, 2026, 10:25 a.m.