Triple
T19744641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | White Mexicans |
E474217
|
entity |
| Predicate | underrepresentedIn |
P56358
|
FINISHED |
| Object | Mexican rural poor |
—
|
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: Mexican rural poor | Statement: [White Mexicans, underrepresentedIn, Mexican rural poor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: underrepresentedIn Context triple: [White Mexicans, underrepresentedIn, Mexican rural poor]
-
A.
areUnderdescribed
Indicates that the entities lack sufficient detail or explanation relative to what is needed or expected.
-
B.
minorityRepresentation
chosen
Indicates the extent to which members of minority groups are present or included within a given group, institution, or context.
-
C.
representsMinorityGroup
Indicates that the subject belongs to or characterizes a group that is numerically, socially, or politically in the minority within a larger population or context.
-
D.
neverRepresentedBy
Indicates that one entity has at no time been represented or acted on behalf of by the other entity.
-
E.
hadRepresentationDisproportionateToPopulation
Indicates that the representation of a group or entity was not proportional to its share of the overall population.
- 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_69d8e51940a0819087bd2996f98da668 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e652923fd48190982c51c39814fd08 |
completed | April 20, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69e5304a7aac8190ac13f75f0c008e45 |
completed | April 19, 2026, 7:43 p.m. |
Created at: April 10, 2026, 1:47 p.m.