Triple
T4863001
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Davis v. Monroe County Board of Education |
E108703
|
entity |
| Predicate | remedyDiscussed |
P51889
|
FINISHED |
| Object | monetary damages under Title IX |
—
|
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: monetary damages under Title IX | Statement: [Davis v. Monroe County Board of Education, remedyDiscussed, monetary damages under Title IX]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: remedyDiscussed Context triple: [Davis v. Monroe County Board of Education, remedyDiscussed, monetary damages under Title IX]
-
A.
remedy
Indicates that one entity serves to cure, alleviate, or counteract a problem, illness, or undesirable condition affecting another entity.
-
B.
remedySought
Indicates that a particular legal or corrective action is being requested as a solution or relief in response to a problem or dispute.
-
C.
discussed
chosen
Indicates that one entity talked about, examined, or debated a topic, issue, or other entity with someone else.
-
D.
consulted
Indicates that one entity sought advice, information, or guidance from another entity.
-
E.
exportTreatment
Indicates the action or process of sending or transferring a treatment (such as a medical, data, or procedural treatment) from one system, location, or context to another for external use or application.
- 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_69bd440b965081908b0557721cae6338 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6d60e47c819094b5fbe883db4c15 |
completed | March 20, 2026, 3:53 p.m. |
| PD | Predicate disambiguation | batch_69bd6c27334481909ba8ac80854f7d8e |
completed | March 20, 2026, 3:47 p.m. |
Created at: March 20, 2026, 1:26 p.m.