Triple
T22081422
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mistress Pat |
E545657
|
entity |
| Predicate | protagonistNickname |
P25214
|
FINISHED |
| Object | Pat |
—
|
NE NERFINISHED |
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: Pat | Statement: [Mistress Pat, protagonistNickname, Pat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pat Context triple: [Mistress Pat, protagonistNickname, Pat]
-
A.
Pat
Pat is the commonly used short form of the given name Patrick, often used as a casual or familiar nickname.
-
B.
Pat
chosen
Pat is a recurring androgynous character from the sketch comedy show "Saturday Night Live," known for the running joke that no one can determine Pat's gender.
-
C.
Pete
Pete is a classic Disney cartoon villain, best known as Mickey Mouse’s burly, antagonistic foe in the Mickey Mouse franchise.
-
D.
Pete
Pete is the nickname of Frank K. Everest Jr., a renowned United States Air Force test pilot and brigadier general known for his high-speed flight records.
-
E.
Pete
Pete is the nickname of Australian racing driver Ian Geoghegan, a prominent figure in touring car racing during the 1960s and 1970s.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b6338481908e6bb0187cdd42af |
completed | April 28, 2026, 9:37 p.m. |
Created at: April 16, 2026, 8:28 p.m.