Triple
T28452341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Council of Non-European Trade Unions |
E716610
|
entity |
| Predicate | ethnoRacialFocus |
P135185
|
FINISHED |
| Object | non-European workers |
—
|
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: non-European workers | Statement: [Council of Non-European Trade Unions, ethnoRacialFocus, non-European workers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ethnoRacialFocus Context triple: [Council of Non-European Trade Unions, ethnoRacialFocus, non-European workers]
-
A.
primaryEthnicFocus
Indicates that something is chiefly oriented toward, concerned with, or designed for a particular ethnic group as its main focus.
-
B.
ethnicGroupInFocus
chosen
Indicates that a particular ethnic group is the primary subject or focal point within a given context, relation, or description.
-
C.
holderEthnicity
Indicates the ethnic background or group to which the holder of something (e.g., a document, account, or item) belongs.
-
D.
sharesEthnicity
Indicates that two entities belong to the same ethnic group or share the same ethnic background.
-
E.
ethnicContrast
Indicates a relationship where two or more entities are contrasted or differentiated based on their ethnic backgrounds or identities.
- 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_69efd6b76f8c8190a7ba908aca280942 |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_69f64e72b5208190869d49fcb3f0a546 |
completed | May 2, 2026, 7:20 p.m. |
| PD | Predicate disambiguation | batch_69f64caede108190a35cc7cbfead866f |
completed | May 2, 2026, 7:12 p.m. |
Created at: April 28, 2026, 1:52 a.m.