Triple
T23894295
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 35 and Ticking |
E600859
|
entity |
| Predicate | featuresCharacterAgeGroup |
P13483
|
FINISHED |
| Object | mid-thirties adults |
—
|
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: mid-thirties adults | Statement: [35 and Ticking, featuresCharacterAgeGroup, mid-thirties adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterAgeGroup Context triple: [35 and Ticking, featuresCharacterAgeGroup, mid-thirties adults]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
portraysAgeGroup
chosen
Indicates that one entity depicts or represents another entity as belonging to a particular age group.
-
C.
groupCharacterization
Indicates how a group as a whole is described or characterized in terms of its shared properties, traits, or defining features.
-
D.
ageGroupInvolved
Indicates that a particular age group participates in, is affected by, or is otherwise involved in the specified event or relationship.
-
E.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid 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_69e295341ac0819080647f2908af793c |
completed | April 17, 2026, 8:16 p.m. |
| NER | Named-entity recognition | batch_69f1cdd857d081908740c4abb246c2ba |
completed | April 29, 2026, 9:22 a.m. |
| PD | Predicate disambiguation | batch_69f1614e24b48190a1c8fb5b7c75ee0f |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 8:25 p.m.