Triple
T8329180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SX5E |
E195031
|
entity |
| Predicate | countryUniverse |
P82127
|
FINISHED |
| Object | eurozone member states |
—
|
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: eurozone member states | Statement: [SX5E, countryUniverse, eurozone member states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: countryUniverse Context triple: [SX5E, countryUniverse, eurozone member states]
-
A.
country2
Indicates a secondary or alternative country associated with an entity, such as a second nationality, location, or jurisdiction.
-
B.
country1
Indicates that the subject entity is a country (or represents a country) in the given context.
-
C.
continentScope
Indicates that something applies within, is limited to, or is defined at the level of a specific continent.
-
D.
continentCountry
Indicates that a country is located on or belongs to a specific continent.
-
E.
countryType
Indicates the classification or category of a country based on a specified typology (e.g., political, economic, or geographic type).
- 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_69ca82e87f2c8190bdb71ee29dfc642d |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7fb812508190aed8a283dacf712e |
completed | March 31, 2026, 8:03 a.m. |
| PD | Predicate disambiguation | batch_69cb70c3231c81909e3d463192c9de22 |
completed | March 31, 2026, 6:59 a.m. |
| PDg | Predicate description generation | batch_69cb76d823b08190a54fadb50660cda5 |
completed | March 31, 2026, 7:25 a.m. |
Created at: March 30, 2026, 5:56 p.m.