Triple
T9255343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mark Farmer |
E222426
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Mark Farmer |
E222426
|
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: Mark Farmer | Statement: [Mark Farmer, name, Mark Farmer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark Farmer Context triple: [Mark Farmer, name, Mark Farmer]
-
A.
Mark Farmer
chosen
Mark Farmer is a British actor best known for his roles in the television series "Grange Hill," "Minder," and "Johnny Jarvis."
-
B.
Ed Farmer
Ed Farmer was an American Major League Baseball pitcher and longtime Chicago White Sox radio broadcaster, best known for his tenure with and contributions to the White Sox organization.
-
C.
Todd Farmer
Todd Farmer is an American screenwriter best known for his work on horror films such as "My Bloody Valentine 3D" and "Jason X."
-
D.
Brian Farmer
Brian Farmer is a notable individual recognized for achievements significant enough to be distinguished among others sharing the surname Farmer.
-
E.
Ken Farmer
Ken Farmer is a notable individual recognized for his achievements and public prominence in his field.
- 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_69ca841e4cd481908e738c74e958eaea |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd06b3c314819096632b8263288aae |
completed | April 1, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d09bde36688190bf66669f585dcee7 |
completed | April 4, 2026, 5:04 a.m. |
Created at: March 30, 2026, 7:31 p.m.