Triple
T24395354
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ashwander v. Tennessee Valley Authority |
E615012
|
entity |
| Predicate | AshwanderRulesCount |
P85168
|
FINISHED |
| Object | seven |
—
|
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: seven | Statement: [Ashwander v. Tennessee Valley Authority, AshwanderRulesCount, seven]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: AshwanderRulesCount Context triple: [Ashwander v. Tennessee Valley Authority, AshwanderRulesCount, seven]
-
A.
numberOfRulesOfAcquisition
Indicates the total count of rules of acquisition associated with or applicable to a given entity.
-
B.
numberOfRulesCompleted
Indicates the count of rules that have been successfully completed or satisfied in a given context.
-
C.
numberOfRulesPlanned
Indicates the planned or intended count of rules associated with an entity or process.
-
D.
numberOfSummonsPerOwner
Indicates the total count of summons associated with each individual owner.
-
E.
hasNumberOfRules
chosen
Indicates the specific count of rules associated with or applicable to an entity.
- 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_69e2d7e509b88190a53155d4f3de45ce |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f294d69b5c81908cf6143374934f5c |
completed | April 29, 2026, 11:31 p.m. |
| PD | Predicate disambiguation | batch_69f287c4a2b48190b80fb7a3c0e9b018 |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 2:04 a.m.