Triple
T8449400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Made in Britain |
E199762
|
entity |
| Predicate | hasProtagonistAge |
P37051
|
FINISHED |
| Object | teenager |
—
|
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: teenager | Statement: [Made in Britain, hasProtagonistAge, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistAge Context triple: [Made in Britain, hasProtagonistAge, teenager]
-
A.
protagonistAge
chosen
Indicates the age of the main character or central figure in a narrative or scenario.
-
B.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
C.
protagonistAgeRelativeToPrequel
Indicates how the protagonist’s age in the current work compares to their age in a preceding prequel story.
-
D.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
E.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
- 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_69ca83170f9081909cd98f55614c6476 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe44707b88190b3d8b30c45ef4496 |
completed | March 31, 2026, 3:12 p.m. |
| PD | Predicate disambiguation | batch_69cbd0f5a3648190beb53a139a2d5482 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:09 p.m.