Triple
T7780976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peggy Bacon |
E221515
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Bacon |
E29977
|
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: Bacon | Statement: [Peggy Bacon, familyName, Bacon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bacon Context triple: [Peggy Bacon, familyName, Bacon]
-
A.
Bacon
chosen
Bacon is a common English surname historically associated with notable figures such as the philosopher and statesman Francis Bacon.
-
B.
Hammon
Hammon is the surname of Becky Hammon, a prominent basketball coach and former professional player.
-
C.
Jambon
Jambon is a surname most notably associated with Belgian politician Jan Jambon.
-
D.
Canadian Bacon
Canadian Bacon is a 1995 political satire film directed by Michael Moore that humorously critiques U.S.–Canada relations and American militarism.
-
E.
BLT
BLT is a Swiss public transport company that operates tram and bus services in and around the Basel region.
- 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_69ca83ebbef881909ac47f789145fef7 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69caa4d6cf9881909f5220437db13cc7 |
completed | March 30, 2026, 4:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69caf5c1f20c81908ae2fc35550b91b5 |
completed | March 30, 2026, 10:14 p.m. |
Created at: March 30, 2026, 4:20 p.m.