Triple
T9699736
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jo Polniaczek |
E234743
|
entity |
| Predicate | marriedTo |
P13
|
FINISHED |
| Object | Rick Bonner |
E815053
|
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: Rick Bonner | Statement: [Jo Polniaczek, marriedTo, Rick Bonner]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Rick Bonner Context triple: [Jo Polniaczek, marriedTo, Rick Bonner]
-
A.
Rick Bonner
chosen
Rick Bonner is a recurring character on the TV sitcom "The Facts of Life," known primarily as a romantic partner of Jo Polniaczek.
-
B.
Gary Bonner
Gary Bonner is a musician best known as a member of the new wave band Tom Tom Club.
-
C.
Tony Bonner
Tony Bonner is an Australian actor best known for his roles in film and television during the 1960s and 1970s, including the series "Skippy the Bush Kangaroo."
-
D.
Anthony Bonner
Anthony Bonner is a translator best known for his English translations of literary works, including those of Jorge Luis Borges.
-
E.
Dave Bannion
Dave Bannion is a tough, morally driven police detective who wages a relentless one-man war against corruption and organized crime in the classic film noir "The Big Heat."
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d6eab0c8190abac1b009d625975 |
completed | April 1, 2026, 10:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d19f7cecd0819081929611b7881102 |
completed | April 4, 2026, 11:32 p.m. |
Created at: March 30, 2026, 8:18 p.m.