Triple
T32163622
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ennui |
E821496
|
entity |
| Predicate | targetAgeGroupRepresented |
P71516
|
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: [Ennui, targetAgeGroupRepresented, teenager]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetAgeGroupRepresented Context triple: [Ennui, targetAgeGroupRepresented, teenager]
-
A.
ageGroupIndicated
Indicates that a specific age range or category is identified or assigned to an entity.
-
B.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
C.
representedAgeLevel
chosen
Indicates that one entity corresponds to, or is categorized under, a particular age level or age group.
-
D.
intendedForAgeGroup
Indicates that something is designed, suitable, or targeted for use by a specific age group.
-
E.
targetedPopulation
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
- 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_69f34905e098819082191a6922a6d607 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fddf721c1481909301a0f379368f10 |
completed | May 8, 2026, 1:04 p.m. |
| PD | Predicate disambiguation | batch_69fddda1ae7c8190b5848ff9a9e39826 |
completed | May 8, 2026, 12:57 p.m. |
Created at: May 1, 2026, 12:33 a.m.