Triple
T20941177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eunicia |
E515722
|
entity |
| Predicate | hasEtymologicalRoot |
P5801
|
FINISHED |
| Object | Eunice |
—
|
NE NERFINISHED |
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: Eunice | Statement: [Eunicia, hasEtymologicalRoot, Eunice]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eunice Context triple: [Eunicia, hasEtymologicalRoot, Eunice]
-
A.
Eunice
chosen
Eunice is a feminine given name of Greek origin, commonly associated with women in English-speaking countries.
-
B.
Eunice (née Unknown)
Eunice (née Unknown) was the wife of Moses Maverick, a 17th-century settler associated with early colonial New England.
-
C.
Eugeneia
Eugeneia is an alternative spelling or variant form of the given name Eugenia, which is derived from Greek and traditionally associated with nobility or good birth.
-
D.
Merope Brown
Merope Brown is a character from the novel and film "National Velvet," one of the children in the Brown family around whom the horse-racing story revolves.
-
E.
Anthea
Anthea is a central character in Ali Smith’s novella "Girl Meets Boy," a modern, queer reimagining of the myth of Iphis.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4fc13408190b06868df03c5c29b |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6f955f0148190ae42278ad5c0f363 |
completed | April 21, 2026, 4:13 a.m. |
Created at: April 16, 2026, 12:50 p.m.