Triple
T4802151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fenner |
E106858
|
entity |
| Predicate | namedForContributionOfEponym |
P53948
|
FINISHED |
| Object | public health |
—
|
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: public health | Statement: [Fenner, namedForContributionOfEponym, public health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: namedForContributionOfEponym Context triple: [Fenner, namedForContributionOfEponym, public health]
-
A.
speciesEponym
Indicates that a species is named in honor of a particular person or entity.
-
B.
hasAwardNamedAfter
Indicates that an entity has an award that is named in honor of another entity.
-
C.
sharesEponymWith
Indicates that two entities are named after the same person, place, or thing (i.e., they share the same eponym).
-
D.
isNamedForEponymRole
chosen
Indicates that one entity bears a name derived from another entity that serves as its eponym or namesake.
-
E.
notableScientist
Indicates that the subject is a scientist who is widely recognized for significant contributions or impact in their field.
- 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_69bd43f6a1e08190bf0a372bfc336ee5 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ff981fc819080d4466c6fe06cf3 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1c43a48190a65e56b1624a2339 |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:23 p.m.