Triple
T24931147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aaron Cross |
E618989
|
entity |
| Predicate | enhancementProgram |
P79042
|
FINISHED |
| Object | Outcome program |
—
|
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: Outcome program | Statement: [Aaron Cross, enhancementProgram, Outcome program]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: enhancementProgram Context triple: [Aaron Cross, enhancementProgram, Outcome program]
-
A.
hasImprovementProgram
chosen
Indicates that an entity is associated with, participates in, or is covered by a program specifically designed to improve its performance, condition, or quality.
-
B.
supportingProgram
Indicates that one program provides assistance, resources, or backing to another program or initiative.
-
C.
developmentProgram
Indicates a structured initiative or plan designed to improve, advance, or build the capabilities, resources, or conditions of a target group, system, or area over time.
-
D.
applicablePrograms
Indicates that certain programs are relevant to, valid for, or can be applied in the context of a given entity or situation.
-
E.
offersProfessionalPrograms
Indicates that an entity provides formal, career-oriented educational or training programs to others.
- 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_69e2fab9edd88190b86004a78a28bc20 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f423b49074819095c7df8610781661 |
completed | May 1, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69f4210130d08190ae30b7943f7a0bbc |
completed | May 1, 2026, 3:41 a.m. |
Created at: April 18, 2026, 5:30 a.m.