Triple
T22596124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fathers and Daughters |
E574684
|
entity |
| Predicate | hasAgeStructure |
P56466
|
FINISHED |
| Object | dual timeline |
—
|
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: dual timeline | Statement: [Fathers and Daughters, hasAgeStructure, dual timeline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAgeStructure Context triple: [Fathers and Daughters, hasAgeStructure, dual timeline]
-
A.
ageGroupStructure
chosen
Indicates how a population or set of entities is distributed across different age groups or age categories.
-
B.
populationAge
Indicates the age or age distribution of a population associated with an entity.
-
C.
containsYoungPopulations
Indicates that the subject includes or is characterized by a significant presence of young or recently formed populations.
-
D.
numberOfAges
Indicates the count of distinct ages associated with an entity or within a specified group or context.
-
E.
hasPopulationType
Indicates that an entity’s population is classified according to a specific type or category (e.g., demographic, biological, or statistical grouping).
- 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_69e245bc11308190b69d794d5d1e0bb6 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f16268cb54819084a0f27ec0473f35 |
completed | April 29, 2026, 1:44 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:50 p.m.