Triple
T747637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Chrysostom |
E15378
|
entity |
| Predicate | epithetMeaning |
P8493
|
FINISHED |
| Object | golden-mouthed |
—
|
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: golden-mouthed | Statement: [John Chrysostom, epithetMeaning, golden-mouthed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: epithetMeaning Context triple: [John Chrysostom, epithetMeaning, golden-mouthed]
-
A.
reasonForEpithet
Indicates the cause, motivation, or circumstance that explains why a particular epithet is applied to an entity.
-
B.
meaningOfPhrase
chosen
Indicates that one entity expresses or defines the semantic content or interpretation of a given phrase.
-
C.
etymologicalRootMeaning
Indicates that one term’s meaning originates from or is derived from the historical or original meaning of another term.
-
D.
etymologyPossibleMeaning
Indicates a possible or hypothesized meaning that an etymological analysis suggests for a word or term.
-
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_69a49358aa308190adbc9b5a0a2adcf9 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a62dd1bc819094a3814654448ae3 |
completed | March 1, 2026, 8:48 p.m. |
| PD | Predicate disambiguation | batch_69a4a4ff10608190bfd60b4a1cb38f7d |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.