Triple
T31308832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bryant's Grocery and Meat Market |
E798406
|
entity |
| Predicate | racialContext |
P169198
|
FINISHED |
| Object | racially segregated South |
—
|
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: racially segregated South | Statement: [Bryant's Grocery and Meat Market, racialContext, racially segregated South]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: racialContext Context triple: [Bryant's Grocery and Meat Market, racialContext, racially segregated South]
-
A.
raceRole
Indicates the specific role, position, or function an entity holds within a race or racing event.
-
B.
racialIdentity
Indicates the relationship between an entity and the racial group or classification with which it is identified or categorized.
-
C.
racialStructure
chosen
Indicates how racial categories or groupings are organized, distributed, or structured within a given context or system.
-
D.
relatedRace
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
-
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_69f224e0bd4c8190aab9b29a73f7aa3c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:14 p.m.