Triple
T13064900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beth Boland |
E329296
|
entity |
| Predicate | fullName |
P16
|
FINISHED |
| Object | Elizabeth Boland |
E329296
|
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 Boland | Statement: [Beth Boland, fullName, Elizabeth Boland]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Elizabeth Boland Context triple: [Beth Boland, fullName, Elizabeth Boland]
-
A.
Elizabeth O’Rourke
Elizabeth O’Rourke is best known as the former wife of acclaimed English actor Terence Stamp.
-
B.
Eileen Durkan
Eileen Durkan is a notable individual associated with the Durkan family name, recognized as a distinguished bearer of the surname.
-
C.
Eileen Connolly
Eileen Connolly is a prominent author and teacher in the field of tarot and esoteric studies, known for her influential books on divination and metaphysics.
-
D.
Beth Boland
chosen
Beth Boland is a suburban mother-turned-criminal mastermind from the TV series "Good Girls," known for orchestrating heists and navigating the dangers of the criminal underworld.
-
E.
Catherine Leahy
Catherine Leahy is a notable individual who shares the surname Leahy, recognized enough to be specifically cited as a bearer of the name.
- 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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980e9bdfc81908eb90fb50597df64 |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd6d6fde508190865a8e3e391fdf5e |
completed | May 8, 2026, 4:58 a.m. |
Created at: April 9, 2026, 8:59 p.m.