Triple
T35414989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amos Barton |
E1023615
|
entity |
| Predicate | evaluatedByNarratorAs |
P49701
|
FINISHED |
| Object | limited but sincere |
—
|
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: limited but sincere | Statement: [Amos Barton, evaluatedByNarratorAs, limited but sincere]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: evaluatedByNarratorAs Context triple: [Amos Barton, evaluatedByNarratorAs, limited but sincere]
-
A.
describedByNarrator
chosen
Indicates that something is presented or explained through the perspective or voice of a narrator.
-
B.
narratorPlayedBy
Indicates that a given narrator character is portrayed or voiced by a specific performer or actor.
-
C.
narratorOf
Indicates that one entity serves as the narrator or storytelling voice for another entity, such as a text, story, or media work.
-
D.
hasNarrativeRole
Indicates that an entity participates in a narrative with a specific functional role (e.g., protagonist, antagonist, narrator) relative to the story.
-
E.
narratorBasedOn
Indicates that a narrative’s narrator is modeled on, inspired by, or derived from a particular real or fictional 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_69f76df54bac8190bd0d3b0eb35cda5f |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7956b1d80819081655f683ce78d5b |
completed | May 3, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.