Triple
T9775084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dan Carter |
E237225
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Daniel William Carter |
E237219
|
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: Daniel William Carter | Statement: [Dan Carter, fullName, Daniel William Carter]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daniel William Carter Context triple: [Dan Carter, fullName, Daniel William Carter]
-
A.
Daniel William Carter
chosen
Daniel William Carter is a legendary New Zealand rugby union fly-half widely regarded as one of the greatest players in the sport’s history.
-
B.
Barrett Smith
Barrett Smith is a musician best known as a member of the bluegrass and Americana band Steep Canyon Rangers.
-
C.
Harrison Carter
Harrison Carter is a fictional character from the classic American television sitcom "Here's Lucy."
-
D.
Lyndon Megarrity
Lyndon Megarrity is an Australian historian and author known for his work on Queensland and North Australian political and social history.
-
E.
Alexander Lester
Alexander Lester is an actor known for portraying the iconic Shakespearean character Lady Macbeth.
- 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_69ca84d975a08190aab25b02a89bdab3 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda13148288190bcbb3b4a066d9fc1 |
completed | April 1, 2026, 10:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1c41789548190ba4f6fdd7fb5192a |
completed | April 5, 2026, 2:08 a.m. |
Created at: March 30, 2026, 8:26 p.m.