Triple
T2177241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cynthia |
E48557
|
entity |
| Predicate | variant |
P4680
|
FINISHED |
| Object | Cyndie |
E48557
|
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: Cyndie | Statement: [Cynthia, variant, Cyndie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cyndie Context triple: [Cynthia, variant, Cyndie]
-
A.
Cynthia
chosen
Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
-
B.
Candice
Candice is a feminine given name commonly used in English-speaking countries, often associated with the meaning "clarity" or "purity."
-
C.
Adrianne
Adrianne is a feminine given name most notably borne by American actress Adrianne Palicki.
-
D.
Sandra
Sandra is the given name of Sandra Day O’Connor, the first woman to serve as a Justice on the United States Supreme Court.
-
E.
Celia Mae
Celia Mae is the one-eyed, snake-haired receptionist at Monsters, Inc. and Mike Wazowski’s girlfriend in the Pixar animated film.
- 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_69a88aa3faa48190995b233af6525815 |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbeecdbc881909982a58568f0b1ed |
completed | March 7, 2026, 6 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71b142208190a09c8e459b200ecb |
completed | March 9, 2026, 7:07 a.m. |
Created at: March 4, 2026, 7:45 p.m.