Triple
T4398869
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oklahoma Department of Transportation |
E99561
|
entity |
| Predicate | appliesFor |
P32549
|
FINISHED |
| Object | federal transportation grants |
—
|
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: federal transportation grants | Statement: [Oklahoma Department of Transportation, appliesFor, federal transportation grants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesFor Context triple: [Oklahoma Department of Transportation, appliesFor, federal transportation grants]
-
A.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
B.
canApplyFor
chosen
Indicates that one entity has the eligibility or permission to submit a request or application for another entity or opportunity.
-
C.
appliesFrom
Indicates that a rule, condition, or effect begins to be applicable starting from a specific point in time or state.
-
D.
appliesAt
Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
-
E.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
- 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_69b345506b408190b0e3dee616738a7d |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352cc4ab081908bc45d2f76cd4da8 |
completed | March 12, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69b34f597998819092477efdedb51427 |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:20 p.m.