Triple
T18210470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delhi, California |
E436017
|
entity |
| Predicate | regionalCharacteristic |
P130244
|
FINISHED |
| Object | largely Hispanic/Latino population |
—
|
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: largely Hispanic/Latino population | Statement: [Delhi, California, regionalCharacteristic, largely Hispanic/Latino population]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: regionalCharacteristic Context triple: [Delhi, California, regionalCharacteristic, largely Hispanic/Latino population]
-
A.
regionalType
Indicates the classification of a region according to its designated type or category within a broader geographic or administrative system.
-
B.
cultureCharacteristic
Indicates that a particular trait, practice, or feature is a defining characteristic of a given culture.
-
C.
regionalOrientation
Indicates how something is directed, aligned, or focused toward a particular geographic region or area.
-
D.
regionalComponent
Indicates that one entity functions as a sub-region or constituent part within the larger geographic or administrative area represented by the other entity.
-
E.
regionallyDistinctFrom
Indicates that two entities differ from each other in characteristics or classification based on their geographic or regional context.
- F. None of above. chosen
Provenance (4 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_69d8b90dba6481908e119eb9aa4ca0cb |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4e228a7fc81909cfcf11cf7ce1360 |
completed | April 19, 2026, 2:09 p.m. |
| PD | Predicate disambiguation | batch_69e4332155d88190b106d0dceb4554af |
completed | April 19, 2026, 1:42 a.m. |
| PDg | Predicate description generation | batch_69e438f684e48190b38c64b58c518b6a |
completed | April 19, 2026, 2:07 a.m. |
Created at: April 10, 2026, 10:32 a.m.