Triple
T4043299
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. T |
E84003
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mr. T |
E84003
|
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: Mr. T | Statement: [Mr. T, name, Mr. T]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mr. T Context triple: [Mr. T, name, Mr. T]
-
A.
Mr. T
Mr. T is the internal codename for the original Macintosh Plus personal computer developed by Apple in the mid-1980s.
-
B.
Mr. T
chosen
Mr. T is an American actor and former professional wrestler best known for his tough-guy persona, distinctive mohawk and gold chains, and iconic roles in 1980s pop culture.
-
C.
Dick York
Dick York was an American actor best known for originating the role of Darrin Stephens on the television series "Bewitched" and for his work in films and radio.
-
D.
Charlie Tahan
Charlie Tahan is an American actor known for his roles in films like "Charlie St. Cloud" and "Super Dark Times" and TV series such as "Ozark" and "Wayward Pines."
-
E.
Rod Kimble
Rod Kimble is the inept but determined amateur stuntman protagonist of the comedy film "Hot Rod," portrayed by Andy Samberg.
- 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_69aed930bd5c819083e7dcc14fc44f69 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb5d759c8190b61fbbe94ffe2bf7 |
completed | March 9, 2026, 4:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5564fb54c81909f40ca1d6f1e521e |
completed | March 14, 2026, 12:36 p.m. |
Created at: March 9, 2026, 3:37 p.m.