Triple
T3511954
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eryximachus |
E74215
|
entity |
| Predicate | usesAnalogyFrom |
P3882
|
FINISHED |
| Object | medicine |
—
|
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: medicine | Statement: [Eryximachus, usesAnalogyFrom, medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAnalogyFrom Context triple: [Eryximachus, usesAnalogyFrom, medicine]
-
A.
viewOnAnalogy
Indicates a relationship where one entity interprets, understands, or evaluates another entity by drawing an analogy to something else.
-
B.
usedAsAnalogFor
chosen
Indicates that one entity is employed as a comparison or illustrative counterpart to help explain, represent, or understand another entity.
-
C.
usedToExplain
Indicates that one entity serves as an explanation or clarification for another entity.
-
D.
analogousTitle
Indicates that one entity has a title or position that corresponds in role, rank, or function to the title or position held by another entity.
-
E.
isUsedToIllustrate
Indicates that one entity serves as an example or demonstration to clarify, explain, or represent another entity.
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc10b6b48190bedfed6d34afc425 |
completed | March 8, 2026, 6:12 p.m. |
| PD | Predicate disambiguation | batch_69adae0e770481908528fa35eda53003 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.