Triple
T2637425
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas's 30th congressional district |
E59779
|
entity |
| Predicate | medianIncomeRankInTexas |
P293
|
FINISHED |
| Object | below state median |
—
|
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: below state median | Statement: [Texas's 30th congressional district, medianIncomeRankInTexas, below state median]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medianIncomeRankInTexas Context triple: [Texas's 30th congressional district, medianIncomeRankInTexas, below state median]
-
A.
medianHouseholdIncomeRank
chosen
Indicates the relative position of a household’s income compared to others, typically ordered from lowest to highest median income.
-
B.
populationRankInTexas
Indicates the relative position of an entity in terms of population size compared to other entities within Texas.
-
C.
medianHouseholdIncome
Indicates the typical (middle) value of income earned by households in a given area, such that half of households earn more and half earn less.
-
D.
rankInUS2010Census
Indicates the numerical position of an entity in the ranking of occurrences within the 2010 United States Census.
-
E.
areaRankInUS
Indicates the relative position of an entity in a ranking of areas within the United States, based on its size.
- 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_69ab4ac8596c8190b34997e73d9e991c |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abd8e3190081908ea828fe79569cc9 |
completed | March 7, 2026, 7:50 a.m. |
| PD | Predicate disambiguation | batch_69abd812849881908f956845a80e0205 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:50 p.m.