Triple
T3699359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United States education system |
E78538
|
entity |
| Predicate | fundingInequalityFactor |
P59
|
FINISHED |
| Object | reliance on local property taxes |
—
|
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: reliance on local property taxes | Statement: [United States education system, fundingInequalityFactor, reliance on local property taxes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fundingInequalityFactor Context triple: [United States education system, fundingInequalityFactor, reliance on local property taxes]
-
A.
fundingContext
Indicates the circumstances, purpose, or conditions under which funding is provided or used in a given relationship or action.
-
B.
fundedBy
Indicates that an entity receives financial support or resources from another entity.
-
C.
possibleAdditionalFunding
Indicates that there is a potential for securing or providing further financial resources beyond what has already been allocated or committed.
-
D.
fundingSpeed
Indicates how quickly financial resources are provided or disbursed within a given funding relationship or process.
-
E.
fundingModel
chosen
Indicates how an entity is financially supported or sustained, such as through specific revenue sources, payment structures, or funding mechanisms.
- 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc513d26c8190bfdf25f62af8c6ca |
completed | March 8, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69adb84dc5808190850aa6975cb09e27 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:26 p.m.