Triple
T22343531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hate Crime Statistics annual report |
E552332
|
entity |
| Predicate | biasCategoryIncluded |
P53933
|
FINISHED |
| Object | race-based bias |
—
|
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: race-based bias | Statement: [Hate Crime Statistics annual report, biasCategoryIncluded, race-based bias]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: biasCategoryIncluded Context triple: [Hate Crime Statistics annual report, biasCategoryIncluded, race-based bias]
-
A.
classificationIncludes
chosen
Indicates that a broader classification category encompasses or contains a specified subclass, member, or element within its scope.
-
B.
endorsementCategory
Indicates the classification or type of endorsement associated with an entity or action.
-
C.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
D.
protectedCategory
Indicates that one entity is classified under a legally or formally recognized group that is granted special protection from discrimination or adverse treatment.
-
E.
cornerCategory
Indicates that something is classified as belonging to a specific type or category of corner.
- 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_69e11e494eec81909c4d2d51f69499d9 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15795b2a881908d6cb8f97443ca17 |
completed | April 29, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e7300c20088190a59e5bf9e70384f3 |
completed | April 21, 2026, 8:06 a.m. |
Created at: April 16, 2026, 8:43 p.m.