Triple
T13333670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clair |
E317633
|
entity |
| Predicate | relatedName |
P3889
|
FINISHED |
| Object | Clarissa |
E644525
|
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: Clarissa | Statement: [Clair, relatedName, Clarissa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Clarissa Context triple: [Clair, relatedName, Clarissa]
-
A.
Clarissa
chosen
Clarissa is a minor but morally reflective character in Alexander Pope’s mock-epic poem "The Rape of the Lock," who delivers a key speech urging Belinda to value virtue over superficial beauty.
-
B.
Clarissa
Clarissa is a character portrayed by American actress Lili Simmons, known for her work in television dramas and thrillers.
-
C.
Clarissa
Clarissa is the given first name of Clara Barton, the pioneering American nurse and founder of the American Red Cross.
-
D.
Pamela
Pamela is the given name of Pam Grier, the pioneering American actress celebrated for her iconic roles in 1970s blaxploitation films and later works like "Jackie Brown."
-
E.
Marianne
Marianne was a 19th-century Dutch princess of the House of Orange-Nassau, known for her independent spirit, unconventional personal life, and extensive patronage of the arts and architecture.
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cff44e08190b9583baf0b626e42 |
completed | April 11, 2026, 12:59 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f36e4cc819093007404ceb5da31 |
completed | May 3, 2026, 10:11 a.m. |
Created at: April 9, 2026, 9:30 p.m.