Triple
T2576481
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynne Thigpen |
E57787
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Cherlynne |
E95375
|
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: Cherlynne | Statement: [Lynne Thigpen, givenName, Cherlynne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cherlynne Context triple: [Lynne Thigpen, givenName, Cherlynne]
-
A.
Madelyn
Madelyn is a feminine given name, often considered a modern variant of Madeline and commonly used in English-speaking countries.
-
B.
Chloe
Chloe is the birth name of Nobel Prize–winning American novelist Toni Morrison, renowned for her powerful explorations of African American life and history.
-
C.
Chloe
Chloe is an epithet of the Greek goddess Demeter, highlighting her aspect as the bringer of new green growth and flourishing vegetation.
-
D.
Charlene
chosen
Charlene is a feminine given name derived from the male name Charles.
-
E.
Tiffani
Tiffani is a given name, typically a modern variant of the name Tiffany used for girls.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd3a606e481909bcea46de468bb99 |
completed | March 7, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af6576a0a8819080d9241801675b19 |
completed | March 10, 2026, 12:27 a.m. |
Created at: March 6, 2026, 9:49 p.m.