Triple
T4886604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anesidora |
E109453
|
entity |
| Predicate | epithetFunction |
P9593
|
FINISHED |
| Object | to stress Demeter’s role as provider of gifts |
—
|
LITERAL 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: to stress Demeter’s role as provider of gifts | Statement: [Anesidora, epithetFunction, to stress Demeter’s role as provider of gifts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epithetFunction Context triple: [Anesidora, epithetFunction, to stress Demeter’s role as provider of gifts]
-
A.
languageOfEpithet
Indicates the language in which an epithet (such as a descriptive or honorary title) is expressed.
-
B.
epithetOrTitle
Indicates that one entity serves as an epithet, honorific, or formal title used to designate or characterize another entity.
-
C.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
D.
reasonForEpithet
chosen
Indicates the cause, motivation, or circumstance that explains why a particular epithet is applied to an entity.
-
E.
honorificEponym
Indicates that one entity serves as an honorific namesake for another, typically recognizing or commemorating the person or entity in whose honor something is named.
- F. None of above.
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_69bd440f71348190b99938e59fb7f9a1 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6e03a7fc8190bcac63f4b19e586e |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2be5e881909f6ec9c3bcde49f3 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:28 p.m.