Triple
T34437031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lone Bean |
E883987
|
entity |
| Predicate | featuresProtagonistAgeGroup |
P121688
|
FINISHED |
| Object | middle grade |
—
|
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: middle grade | Statement: [Lone Bean, featuresProtagonistAgeGroup, middle grade]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresProtagonistAgeGroup Context triple: [Lone Bean, featuresProtagonistAgeGroup, middle grade]
-
A.
hasProtagonistAgeRange
chosen
Indicates that a work’s main character falls within a specified age range.
-
B.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
-
C.
hasAgeingProtagonist
Indicates that the work features a main character who is experiencing aging or the later stages of life as a central aspect of their role or development.
-
D.
hasChildProtagonist
Indicates that the work features a child as its main or central character.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
- 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_69f349c548d88190978e2a82502c03d0 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a032d9200448190a2adcc5ee48bff01 |
completed | May 12, 2026, 1:39 p.m. |
| PD | Predicate disambiguation | batch_6a032c9f41f08190b1c60b0afbbac01a |
completed | May 12, 2026, 1:35 p.m. |
Created at: May 1, 2026, 2 a.m.