Triple
T15072993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anthony Award |
E379927
|
entity |
| Predicate | fieldOfEponym |
P117207
|
FINISHED |
| Object | mystery and crime fiction |
—
|
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: mystery and crime fiction | Statement: [Anthony Award, fieldOfEponym, mystery and crime fiction]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldOfEponym Context triple: [Anthony Award, fieldOfEponym, mystery and crime fiction]
-
A.
eponymKnownFor
Indicates that a person or entity is widely recognized or named as the source or inspiration for something else (such as a concept, place, or object).
-
B.
speciesEponym
Indicates that a species is named in honor of a particular person or entity.
-
C.
sharesEponymWith
Indicates that two entities are named after the same person, place, or thing (i.e., they share the same eponym).
-
D.
eponymFor
Indicates that one entity gives its name to another entity, which is then named after it.
-
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. chosen
Provenance (4 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_69d85cd7683881908d405c1b5d7b4f7f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dff7fa0570819088a97b28173154cd |
completed | April 15, 2026, 8:41 p.m. |
| PD | Predicate disambiguation | batch_69deb95a182081908fffc4402b02a394 |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec71e8dcc81908badc834b6ccf273 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:02 a.m.