Triple
T4170487
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saorview |
E84549
|
entity |
| Predicate | intendedCoveragePopulationShare |
P54494
|
FINISHED |
| Object | approximately 98 percent of population |
—
|
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: approximately 98 percent of population | Statement: [Saorview, intendedCoveragePopulationShare, approximately 98 percent of population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: intendedCoveragePopulationShare Context triple: [Saorview, intendedCoveragePopulationShare, approximately 98 percent of population]
-
A.
targetedPopulation
Indicates the group of individuals or entities that an action, intervention, or effect is specifically directed toward.
-
B.
supportedPopulation
Indicates that one entity provides assistance, resources, or services to sustain or benefit a specified group of people.
-
C.
usedByPopulation
Indicates that something is utilized or consumed by a specific population or group of people.
-
D.
hasServiceAreaPopulation
Indicates that an entity has a service area characterized by a specific population size or count.
-
E.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
- F. None of above. chosen
Provenance (4 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c87cc88190a9ec3712db18a8a7 |
completed | March 9, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69af018fb0948190a9701b2e8e5d9bac |
completed | March 9, 2026, 5:21 p.m. |
| PDg | Predicate description generation | batch_69af01ee94ec8190aa6dde54d4571c04 |
completed | March 9, 2026, 5:22 p.m. |
Created at: March 9, 2026, 3:45 p.m.