Triple
T9186003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Betsy |
E220459
|
entity |
| Predicate | isDiminutiveOf |
P456
|
FINISHED |
| Object | Elizabeth |
unclear NED1
|
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: Elizabeth | Statement: [Betsy, isDiminutiveOf, Elizabeth]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Context triple: [Betsy, isDiminutiveOf, Elizabeth]
-
A.
Elizabeth
Elizabeth is the birth name of American actress and singer Betty Hutton, a popular Hollywood star of the 1940s and 1950s.
-
B.
Elizabeth
Elizabeth is the first name of Elizabeth Bishop, the acclaimed American poet known for her precise language and vivid imagery.
-
C.
Elizabeth
Elizabeth was the given name of Elizabeth Batts Cook, the wife of British explorer Captain James Cook.
-
D.
Elizabeth
Elizabeth is a comedic, high-strung fiancée character in the 1974 Mel Brooks film "Young Frankenstein," known for her dramatic personality and memorable scenes.
-
E.
Elizabeth
Elizabeth is the birth name of American actress and comedian Ellie Kemper, known for her roles in "The Office" and "Unbreakable Kimmy Schmidt."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
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_69ca83e6d77c81909862b7afef56b1bf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccc31a52508190a83ccd76f3aa039b |
completed | April 1, 2026, 7:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d0b1a200288190a5545ca79bac017f |
completed | April 4, 2026, 6:37 a.m. |
Created at: March 30, 2026, 7:24 p.m.