Triple
T4117484
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cynthia McKinney |
E90327
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cynthia |
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: Cynthia | Statement: [Cynthia McKinney, givenName, Cynthia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cynthia Context triple: [Cynthia McKinney, givenName, Cynthia]
-
A.
Cynthia
chosen
Cynthia is a common feminine given name used in various cultures, often associated with the Greek moon goddess Artemis.
-
B.
Cindy
Cindy is a fictional character from the short-lived 1970s American sitcom "Blansky's Beauties," which followed the lives of Las Vegas showgirls.
-
C.
Tricia
Tricia is a feminine given name commonly used as a shortened or informal form of Patricia.
-
D.
Adrienne
Adrienne is a feminine given name of French origin, commonly used in English- and French-speaking countries.
-
E.
Patricia
Patricia is a feminine given name of Latin origin, commonly used in English-speaking countries.
- 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_69aed95c080881908125e30c5dcdc6f8 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af01f347f8819080dd250398474d7e |
completed | March 9, 2026, 5:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b59608650c81908ebc47bbbbfaf6be |
completed | March 14, 2026, 5:08 p.m. |
Created at: March 9, 2026, 3:41 p.m.