Triple
T880982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European Parliament (Luxembourg seat) |
E19025
|
entity |
| Predicate | roleInInstitution |
P13957
|
FINISHED |
| Object | administrative centre |
—
|
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: administrative centre | Statement: [European Parliament (Luxembourg seat), roleInInstitution, administrative centre]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roleInInstitution Context triple: [European Parliament (Luxembourg seat), roleInInstitution, administrative centre]
-
A.
hasEducationalRole
Indicates that an entity holds a specific function, position, or responsibility within an educational context or setting.
-
B.
includesInstitution
Indicates that one entity contains, encompasses, or has as a member a particular institution.
-
C.
hasOrganizationalRole
chosen
Indicates that an entity holds a specific role, position, or function within an organization.
-
D.
hasAcademicAffiliation
Indicates that an entity is formally associated with an academic institution, such as through employment, enrollment, or official collaboration.
-
E.
associatedWithInstitution
Indicates that an entity has a formal or recognized connection or affiliation with an institution.
- 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_69a4939c32488190a7ccd41cf0abb22b |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4accb653c81909fe0753f78145be9 |
completed | March 1, 2026, 9:16 p.m. |
| PD | Predicate disambiguation | batch_69a4aa8eca748190b58e0f08b30fba43 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.