Triple
T38490402
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montgomery City Lines |
E918038
|
entity |
| Predicate | usedRacialSegregationPolicies |
P135760
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Montgomery City Lines, usedRacialSegregationPolicies, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedRacialSegregationPolicies Context triple: [Montgomery City Lines, usedRacialSegregationPolicies, yes]
-
A.
segregationEra
Indicates a period or context in which entities are subject to racially discriminatory separation or unequal treatment under segregation policies.
-
B.
raceSegregationStatus
chosen
Indicates whether entities are separated, treated differently, or organized based on racial categories or distinctions.
-
C.
stanceOnSegregation
Indicates a person or group’s expressed position, attitude, or viewpoint regarding racial or social segregation.
-
D.
racialPolicyHistory
Indicates the historical record of racial policies that have been applied to or associated with an entity over time.
-
E.
segregationBasis
Indicates the criterion or characteristic used as the basis for separating or distinguishing one group or set from another.
- 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_69f76e9894208190a129a553a60ca58c |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcd313e61c8190b174b331365b803f |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f6b2e08190bf0300ae7c9ae67a |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:31 p.m.