Triple
T34100044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ara Parseghian Medical Research Fund |
E874539
|
entity |
| Predicate | focusesOnConditionType |
P31662
|
FINISHED |
| Object | rare genetic disorder |
—
|
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: rare genetic disorder | Statement: [Ara Parseghian Medical Research Fund, focusesOnConditionType, rare genetic disorder]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: focusesOnConditionType Context triple: [Ara Parseghian Medical Research Fund, focusesOnConditionType, rare genetic disorder]
-
A.
typeOfCondition
Indicates that one condition is a specific kind, category, or subtype of another condition.
-
B.
scopeCondition
Indicates the specific conditions or constraints under which something is valid, applicable, or in effect within a given scope.
-
C.
focusType
Indicates the specific kind or category of focus or attention that is being applied to or associated with an entity or interaction.
-
D.
focusesOn
Indicates that one entity directs its attention, effort, or primary activity toward another entity or specific subject.
-
E.
targetedCondition
chosen
Indicates that an action, intervention, or entity is specifically directed toward affecting, treating, or addressing a particular condition.
- 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_69f349a735208190a1dbfb1c2a121059 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 1, 2026, 1:53 a.m.