Triple
T14697249
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | "Fallen cold and dead" |
E345194
|
entity |
| Predicate | belongsToAuthorNationality |
P76869
|
FINISHED |
| Object | American literature |
—
|
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: American literature | Statement: ["Fallen cold and dead", belongsToAuthorNationality, American literature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToAuthorNationality Context triple: ["Fallen cold and dead", belongsToAuthorNationality, American literature]
-
A.
authorNationality
Indicates the relationship between an author and the country or nationality with which that author is identified.
-
B.
appearsInWorkByAuthorNationality
chosen
Indicates that an entity appears in a work created by an author of a specified nationality.
-
C.
associatedWithNationality
Indicates that one entity has a connection or affiliation with the nationality of another entity.
-
D.
associatedComposerNationality
Indicates that there is a relationship between a composer and a specific nationality with which that composer is identified or associated.
-
E.
coAuthorNationality
Indicates that two or more co-authors of a work share the same nationality or have nationalities being related in the context of their co-authorship.
- 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_69d822e4a8c08190a155df736bb7bc13 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb58855e081908b38f9515db5677f |
completed | April 14, 2026, 9:45 p.m. |
| PD | Predicate disambiguation | batch_69de657c57ec8190ae0b9bb79a514566 |
completed | April 14, 2026, 4:04 p.m. |
Created at: April 10, 2026, 1:28 a.m.