Triple
T27566044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Department of Labour and Social Security Law |
E695902
|
entity |
| Predicate | alsoStudies |
P163287
|
FINISHED |
| Object | European Union labour law |
—
|
NE NERFINISHED |
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: European Union labour law | Statement: [Department of Labour and Social Security Law, alsoStudies, European Union labour law]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alsoStudies Context triple: [Department of Labour and Social Security Law, alsoStudies, European Union labour law]
-
A.
alsoStudies
chosen
Indicates that an entity engages in studying an additional subject or field alongside another already being studied.
-
B.
alsoStudied
Indicates that an entity pursued additional studies in another subject, field, or institution besides a primary one.
-
C.
relatedStudy
Indicates that one study is connected or relevant to another study, typically through shared topics, methods, or findings.
-
D.
studiesFeature
Indicates that an entity conducts research or examination on a particular feature or characteristic of something.
-
E.
studiesFor
Indicates that one entity engages in studying or academic preparation with the purpose of achieving or supporting another entity (such as a goal, exam, or qualification).
- 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_69ef53891af88190a193c5e2a1dac9b1 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f63894e5848190aec428392562ab06 |
completed | May 2, 2026, 5:47 p.m. |
| PD | Predicate disambiguation | batch_69f6370c8c7c8190a02ea82847bb6e76 |
completed | May 2, 2026, 5:40 p.m. |
Created at: April 27, 2026, 1:41 p.m.