Triple
T12317390
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ten Indians |
E293635
|
entity |
| Predicate | hasMainCharacterAgeRange |
P2736
|
FINISHED |
| Object | adolescent |
—
|
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: adolescent | Statement: [Ten Indians, hasMainCharacterAgeRange, adolescent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMainCharacterAgeRange Context triple: [Ten Indians, hasMainCharacterAgeRange, adolescent]
-
A.
ageRange
chosen
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
B.
containsAge
Indicates that one entity includes or specifies the age value or age-related information of another entity.
-
C.
isAdultCharacter
Indicates that a character has reached adulthood, typically meeting the age or maturity criteria defining an adult within the given context.
-
D.
supportsAgeRange
Indicates that one entity is compatible with, valid for, or designed to accommodate a specified range of ages.
-
E.
ageLimitYears
Indicates the maximum allowed age, expressed in years, for which something is valid, permitted, or applicable.
- 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_69d6ab6a2b50819082f6aedd32ed608a |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d93f621570819091ee1db2609233ea |
completed | April 10, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69d93ec5be788190b82d2edc6a0f1095 |
completed | April 10, 2026, 6:17 p.m. |
Created at: April 8, 2026, 9:53 p.m.