Triple
T10196646
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LLFPA |
E238778
|
entity |
| Predicate | raceEqualityImpact |
P10927
|
FINISHED |
| Object | addresses race-based pay discrimination |
—
|
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: addresses race-based pay discrimination | Statement: [LLFPA, raceEqualityImpact, addresses race-based pay discrimination]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raceEqualityImpact Context triple: [LLFPA, raceEqualityImpact, addresses race-based pay discrimination]
-
A.
raceRole
Indicates the specific role, position, or function an entity holds within a race or racing event.
-
B.
racePolicy
Indicates that an entity has established rules, practices, or guidelines governing how races or competitive events are conducted or managed.
-
C.
affectedEthnicGroup
chosen
Indicates that a particular ethnic group is impacted or influenced by an event, condition, policy, or action.
-
D.
relatedRace
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
-
E.
racialIdentity
Indicates the relationship between an entity and the racial group or classification with which it is identified or categorized.
- 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_69ca84e1ea088190b38162e43d4cfa8f |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdedcaf6688190938d8e56e29493eb |
completed | April 2, 2026, 4:17 a.m. |
| PD | Predicate disambiguation | batch_69cd7c8477648190bc55c56aeec507d3 |
completed | April 1, 2026, 8:13 p.m. |
Created at: March 30, 2026, 9:13 p.m.