Triple
T10918845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hårga |
E257890
|
entity |
| Predicate | ageStructure |
P56466
|
FINISHED |
| Object | life divided into four 18-year seasons |
—
|
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: life divided into four 18-year seasons | Statement: [Hårga, ageStructure, life divided into four 18-year seasons]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageStructure Context triple: [Hårga, ageStructure, life divided into four 18-year seasons]
-
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.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
D.
numberOfAges
Indicates the count of distinct ages associated with an entity or within a specified group or context.
-
E.
populationClass
Indicates a categorical classification of a population based on shared characteristics, status, or demographic criteria.
- 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_69d6aa864ed88190818280ab6791d065 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d77080317881909fc50ac3576cefa8 |
completed | April 9, 2026, 9:25 a.m. |
| PD | Predicate disambiguation | batch_69d72e799f808190b6ab64fc7586a303 |
completed | April 9, 2026, 4:43 a.m. |
Created at: April 8, 2026, 9:22 p.m.