Triple
T24857470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Carlos Argentino Daneri |
E622065
|
entity |
| Predicate | perceptionByNarrator |
P49701
|
FINISHED |
| Object | ridiculous |
—
|
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: ridiculous | Statement: [Carlos Argentino Daneri, perceptionByNarrator, ridiculous]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: perceptionByNarrator Context triple: [Carlos Argentino Daneri, perceptionByNarrator, ridiculous]
-
A.
describedByNarrator
chosen
Indicates that something is presented or explained through the perspective or voice of a narrator.
-
B.
narratorBasedOn
Indicates that a narrative’s narrator is modeled on, inspired by, or derived from a particular real or fictional entity.
-
C.
settingOfNarrator
Indicates that a given location or context serves as the narrative setting in which the narrator’s story or perspective takes place.
-
D.
narratorOf
Indicates that one entity serves as the narrator or storytelling voice for another entity, such as a text, story, or media work.
-
E.
narratorRole
Indicates that one entity serves as the narrator of another entity (such as a story, text, or media work), specifying the narrative role or function it performs.
- 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_69e2fac350d08190b3affde1b451a8c5 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 5:21 a.m.