Triple
T12088874
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sophia Willard Dana Ripley |
E287883
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Ripley |
E823020
|
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: Ripley | Statement: [Sophia Willard Dana Ripley, familyName, Ripley]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ripley Context triple: [Sophia Willard Dana Ripley, familyName, Ripley]
-
A.
Ripley
Ripley is a small town in the Amber Valley district of Derbyshire, England, known historically for its role in the region’s coal mining and industrial development.
-
B.
Ripley
Ripley is a small rural community located within Bruce County in southwestern Ontario, Canada.
-
C.
Ripley
chosen
Ripley is a surname most notably associated with various public figures in entertainment, sports, and literature.
-
D.
Ripley
Ripley is a television miniseries adaptation of Patricia Highsmith’s Tom Ripley novels, starring Andrew Scott as the charismatic con artist Tom Ripley.
-
E.
Ripley
Ripley is a village and civil parish in Surrey, England, known for its historic high street, village green, and traditional English character.
- 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_69d6ab4964708190850585628b287b0c |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d915161f848190a6355c1e372eadaa |
completed | April 10, 2026, 3:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f5f66b2eb48190bae469d1dd82b119 |
completed | May 2, 2026, 1:04 p.m. |
Created at: April 8, 2026, 9:48 p.m.