Triple
T3412790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cajun |
E71935
|
entity |
| Predicate | demographicEstimate |
P3412
|
FINISHED |
| Object | hundreds of thousands in Louisiana |
—
|
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: hundreds of thousands in Louisiana | Statement: [Cajun, demographicEstimate, hundreds of thousands in Louisiana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: demographicEstimate Context triple: [Cajun, demographicEstimate, hundreds of thousands in Louisiana]
-
A.
hasPopulationApproximate
chosen
Indicates that an entity has an estimated or approximate population size, rather than an exact count.
-
B.
approximatePopulationTrend
Indicates an estimated or generalized pattern of how a population changes over time (e.g., increasing, decreasing, or stable) rather than an exact count.
-
C.
hasPopulationAsOf
Indicates that a population count is associated with a specific point or date in time when that population figure was valid or recorded.
-
D.
demographicScope
Indicates the specific population group or demographic segment to which something (e.g., a policy, study, product, or service) is targeted or applicable.
-
E.
permanentPopulation
Indicates that an entity has a stable, long-term resident population rather than a temporary or transient presence.
- 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_69ad85ac312481909e7027ced1456a9f |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb90ba83c81909abdcddb334e64f6 |
completed | March 8, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69adadfcbc38819080852c18240451c5 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:15 p.m.