Triple
T21651906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | British officer Cotton (epithet cottoni) |
E534358
|
entity |
| Predicate | eponymicEpithet |
P47121
|
FINISHED |
| Object | cottoni |
—
|
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: cottoni | Statement: [British officer Cotton (epithet cottoni), eponymicEpithet, cottoni]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eponymicEpithet Context triple: [British officer Cotton (epithet cottoni), eponymicEpithet, cottoni]
-
A.
eponymFor
chosen
Indicates that one entity gives its name to another entity, which is then named after it.
-
B.
epithetAppliedBy
Indicates that a particular epithet or descriptive label is used or assigned by a specific agent to a target entity.
-
C.
specificEpithet
Indicates the taxonomic relationship where a specific epithet designates the species-level name within a binomial scientific name, distinguishing one species from others in the same genus.
-
D.
epithetScope
Indicates that an epithet (a descriptive label or phrase) applies specifically within a defined contextual scope or domain for the referenced entity or relation.
-
E.
hasMeaningOfEpithet
Indicates that one entity expresses or conveys the meaning or sense of another entity’s epithet.
- 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_69e0c466aec88190ba39c7543dbc8ba2 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ef591594a08190bf0ddd0a0c0922ba |
completed | April 27, 2026, 12:39 p.m. |
| PD | Predicate disambiguation | batch_69e696826c3c81909270791e79760937 |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:36 p.m.