Triple
T31856960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rocket |
E813222
|
entity |
| Predicate | hasAgeRangeInFilm |
P121688
|
FINISHED |
| Object | teenager to young adult |
—
|
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 to young adult | Statement: [Rocket, hasAgeRangeInFilm, teenager to young adult]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeRangeInFilm Context triple: [Rocket, hasAgeRangeInFilm, teenager to young adult]
-
A.
hasProtagonistAgeRange
chosen
Indicates that a work’s main character falls within a specified age range.
-
B.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
C.
hasApproximateAgeRange
Indicates that one entity is associated with another entity representing an estimated or non-exact span of ages.
-
D.
supportsAgeRange
Indicates that one entity is compatible with, valid for, or designed to accommodate a specified range of ages.
-
E.
existsInAge
Indicates that an entity is present, valid, or active during a specified age or time period.
- 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_69f348ebf32881908d9439646933dc76 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b21e7e088190832a3db585daea1c |
completed | May 3, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69f6b14faf608190a25b977c0740729c |
completed | May 3, 2026, 2:22 a.m. |
Created at: April 30, 2026, 11:52 p.m.