Triple
T16989714
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Trade Disputes and Trade Unions Act 1946 |
E412159
|
entity |
| Predicate | affectedActors |
P29288
|
FINISHED |
| Object | trade unions in the United Kingdom |
—
|
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: trade unions in the United Kingdom | Statement: [Trade Disputes and Trade Unions Act 1946, affectedActors, trade unions in the United Kingdom]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: affectedActors Context triple: [Trade Disputes and Trade Unions Act 1946, affectedActors, trade unions in the United Kingdom]
-
A.
affectedArea
Indicates the specific region or extent over which an event, condition, or influence has an impact.
-
B.
affectedEntity
chosen
Indicates that an entity is the one that is impacted, influenced, or acted upon as a result of an event, action, or process.
-
C.
affectedPeople
Indicates the people who are impacted or influenced by a particular event, action, or condition.
-
D.
affectedPerson
Indicates that a particular person is impacted or influenced by an event, action, or condition.
-
E.
affectedCompany
Indicates that a company is impacted or influenced by a particular event, action, or entity.
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d27fbaa0819099f79fc74d211647 |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:32 a.m.