Triple
T38178047
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Badger, Minnesota |
E1000269
|
entity |
| Predicate | hasPerCapitaIncome2000 |
P94361
|
FINISHED |
| Object | $15,000 |
—
|
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: $15,000 | Statement: [Badger, Minnesota, hasPerCapitaIncome2000, $15,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPerCapitaIncome2000 Context triple: [Badger, Minnesota, hasPerCapitaIncome2000, $15,000]
-
A.
perCapitaIncome2000USD
chosen
Indicates the amount of income earned on average per person, measured in U.S. dollars for the year 2000.
-
B.
medianFamilyIncome2000USD
Indicates the median income earned by families in the year 2000, expressed in U.S. dollars.
-
C.
householdsCensus2000
Indicates the number of households recorded in the 2000 census for a given geographic or administrative unit.
-
D.
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.
-
E.
householdIncome
Indicates the monetary income received by a household, typically over a specified period such as a year.
- 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_69f76daaace48190a38cee37f8ce343f |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fec8aef1d8819094c7fd7074038e6b |
completed | May 9, 2026, 5:39 a.m. |
| PD | Predicate disambiguation | batch_69fec639876481908efd84a3631a4271 |
completed | May 9, 2026, 5:29 a.m. |
Created at: May 3, 2026, 4:29 p.m.