Triple
T14201959
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tuskegee syphilis study |
E351984
|
entity |
| Predicate | benefitsPromisedToParticipants |
P487
|
FINISHED |
| Object | free medical exams |
—
|
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: free medical exams | Statement: [Tuskegee syphilis study, benefitsPromisedToParticipants, free medical exams]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitsPromisedToParticipants Context triple: [Tuskegee syphilis study, benefitsPromisedToParticipants, free medical exams]
-
A.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
B.
benefitAppliesTo
Indicates that a particular benefit is applicable to, or valid for, a specified entity or context.
-
C.
benefits
chosen
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
D.
benefitStructure
Indicates a relationship where one entity defines, organizes, or governs the benefits (such as advantages, compensations, or perks) provided to or associated with another entity.
-
E.
benefitProgramInvolved
Indicates that a benefit program participates in, is associated with, or plays a role in the referenced situation or relationship.
- 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_69d827894ac0819097803e57f3227b23 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61f589a08190b71ad4e69d92ffd0 |
completed | April 14, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69de05bcd7d48190a4848d9320404aa6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 1:05 a.m.