Triple
T21624889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ty Michael Carter |
E533674
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Ty |
—
|
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: Ty | Statement: [Ty Michael Carter, givenName, Ty]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ty Context triple: [Ty Michael Carter, givenName, Ty]
-
A.
Ty
chosen
Ty is the first name of American musician and songwriter Ty Segall, known for his prolific work in garage and psychedelic rock.
-
B.
TY
TY is the vehicle registration code used on license plates for County Tyrone in Northern Ireland.
-
C.
Y Ty
Y Ty is a remote highland commune in northern Vietnam renowned for its terraced rice fields, misty mountain landscapes, and ethnic minority culture.
-
D.
Ti
Ti was an ancient Egyptian official of the Fifth Dynasty, known from his elaborately decorated mastaba tomb at Saqqara that provides important insights into Old Kingdom life and art.
-
E.
Tu
Tu Youyou is a Chinese pharmaceutical chemist and Nobel laureate renowned for discovering the antimalarial drug artemisinin.
- 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_69e0c464fba881908d0ff2ac80511ce1 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef52121c3c8190b9b4d862ed247c71 |
completed | April 27, 2026, 12:09 p.m. |
Created at: April 16, 2026, 6:34 p.m.