Triple
T20244113
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rose Granger-Weasley |
E498375
|
entity |
| Predicate | ageAtStartOfCursedChild |
P139373
|
FINISHED |
| Object | around 11 years old |
—
|
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: around 11 years old | Statement: [Rose Granger-Weasley, ageAtStartOfCursedChild, around 11 years old]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtStartOfCursedChild Context triple: [Rose Granger-Weasley, ageAtStartOfCursedChild, around 11 years old]
-
A.
playedByChildActor
Indicates that a role or character is portrayed by an actor who is a child at the time of performance.
-
B.
ageInFirstFilm
Indicates the age a person was when they appeared in their first film.
-
C.
cameOfAge
Indicates that an entity reached the age or stage of maturity at which it is considered an adult or fully responsible.
-
D.
typicallyIssuedAtAge
Indicates the age at which something is most commonly or customarily issued to an individual.
-
E.
protagonistAge
Indicates the age of the main character or central figure in a narrative or scenario.
- F. None of above. chosen
Provenance (4 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_69da6274c58c81909c646eabed6f4f30 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e67170aa248190922fc845d2265ae3 |
completed | April 20, 2026, 6:33 p.m. |
| PD | Predicate disambiguation | batch_69e55b1b23f88190bdcbe2f81dd226dd |
completed | April 19, 2026, 10:45 p.m. |
| PDg | Predicate description generation | batch_69e56702ad04819099c1c08f28d16809 |
completed | April 19, 2026, 11:36 p.m. |
Created at: April 11, 2026, 11:40 p.m.