Triple
T3586572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rachel Marron |
E75923
|
entity |
| Predicate | loveInterest |
P7325
|
FINISHED |
| Object | Frank Farmer |
E55812
|
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: Frank Farmer | Statement: [Rachel Marron, loveInterest, Frank Farmer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Farmer Context triple: [Rachel Marron, loveInterest, Frank Farmer]
-
A.
Frank Farmer
chosen
Frank Farmer is the stoic former Secret Service agent turned professional bodyguard who is hired to protect a famous singer in the film "The Bodyguard."
-
B.
Brian Farmer
Brian Farmer is a notable individual recognized for achievements significant enough to be distinguished among others sharing the surname Farmer.
-
C.
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.
-
D.
Mark Farmer
Mark Farmer is a British actor best known for his roles in the television series "Grange Hill," "Minder," and "Johnny Jarvis."
-
E.
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."
- 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_69ad85d6dc3c8190b491b79b83e25461 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc137eb708190809cd52b6deb227c |
completed | March 8, 2026, 6:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b44efa419481908f07a9367adc4e42 |
completed | March 13, 2026, 5:52 p.m. |
Created at: March 8, 2026, 3:22 p.m.