Triple
T9169839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gender Inequality Index |
E220053
|
entity |
| Predicate | aggregationLevel |
P67289
|
FINISHED |
| Object | country level |
—
|
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: country level | Statement: [Gender Inequality Index, aggregationLevel, country level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aggregationLevel Context triple: [Gender Inequality Index, aggregationLevel, country level]
-
A.
aggregationProperty
Indicates that one entity serves as an aggregation or summary of values or instances associated with another entity.
-
B.
dataCollectionLevel
chosen
Indicates the extent or granularity at which data is gathered or recorded within a given context or system.
-
C.
ordinationLevel
Indicates the hierarchical rank or degree of authority assigned to an entity within an ordered or structured system.
-
D.
dataAggregation
Indicates the process by which multiple data points or datasets are combined into a summarized or consolidated form.
-
E.
fragmentationLevel
Indicates the degree to which something is broken into smaller, separate parts or segments.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccaae23f048190847f12317be925b1 |
completed | April 1, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:22 p.m.