Triple
T12384849
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nancy Greene |
E295836
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Nancy Greene |
E295836
|
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: Nancy Greene | Statement: [Nancy Greene, name, Nancy Greene]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nancy Greene Context triple: [Nancy Greene, name, Nancy Greene]
-
A.
Nancy Greene
chosen
Nancy Greene is a celebrated Canadian alpine ski racer and Olympic gold medalist who later became a prominent national sports figure and senator.
-
B.
Patricia Greene
Patricia Greene is a British actress best known for her long-running role as Jill Archer in the BBC radio soap opera "The Archers."
-
C.
Nancy Grey
Nancy Grey is a fictional character from the film "Red Dog," contributing to the story’s emotional depth and relationships surrounding the legendary kelpie.
-
D.
Patty Greene
Patty Greene is the socially awkward yet witty teenage protagonist of the early 1980s sitcom "Square Pegs," known for her attempts to fit into high school cliques.
-
E.
Nancy Montgomery
Nancy Montgomery is a pivotal character in Margaret Atwood’s novel "Alias Grace," serving as the housekeeper and mistress whose murder becomes central to the story’s mystery.
- 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_69d6ad9e653c8190b1473c860ee53dae |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d93fbc3f608190b0ee3c4f304a94db |
completed | April 10, 2026, 6:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f65ea28b508190a2467b9af195e4ed |
completed | May 2, 2026, 8:29 p.m. |
Created at: April 8, 2026, 9:54 p.m.