Triple
T20196774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 924 Gilman Street |
E493104
|
entity |
| Predicate | discriminationPolicy |
P134254
|
FINISHED |
| Object | anti-racist |
—
|
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: anti-racist | Statement: [924 Gilman Street, discriminationPolicy, anti-racist]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: discriminationPolicy Context triple: [924 Gilman Street, discriminationPolicy, anti-racist]
-
A.
discriminationStatus
Indicates whether an entity is subject to, engaged in, or affected by discriminatory treatment based on protected or distinguishing characteristics.
-
B.
addressesDiscriminationAgainst
chosen
Indicates that an action, policy, or measure is specifically aimed at confronting, reducing, or eliminating discrimination directed toward certain individuals or groups.
-
C.
prohibitsDiscriminationBasis
Indicates that an entity forbids discriminatory treatment based on specified characteristics or grounds.
-
D.
discriminatoryLaw
Indicates that a law treats individuals or groups differently in a way that is biased, unfair, or based on protected characteristics such as race, gender, or religion.
-
E.
discriminatedAgainst
Indicates that one entity treats another unfairly or unequally based on a particular characteristic, such as race, gender, or other protected attributes.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad99d50819090ddb7b546c65321 |
completed | April 20, 2026, 6:05 p.m. |
| PD | Predicate disambiguation | batch_69e55b14c9d8819095453d0504d9222f |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:37 p.m.