Triple
T524151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Common Ground Foundation |
E10880
|
entity |
| Predicate | programModel |
P2192
|
FINISHED |
| Object | after-school programs |
—
|
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: after-school programs | Statement: [Common Ground Foundation, programModel, after-school programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: programModel Context triple: [Common Ground Foundation, programModel, after-school programs]
-
A.
program
Indicates that an entity creates, writes, or develops a computer program or software application.
-
B.
programType
chosen
Indicates the category or kind of program to which an entity belongs or with which it is associated.
-
C.
implementedProgram
Indicates that an entity has created, developed, or put into operation a particular program or software system.
-
D.
softwareModel
Indicates that one entity serves as a software-based representation or abstraction (a model) of another entity or system.
-
E.
componentProgram
Indicates that one entity is a component or module that forms part of a larger program or software system represented by the other 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b656c08190b387f21b06d99e68 |
completed | Feb. 28, 2026, 1:46 p.m. |
| PD | Predicate disambiguation | batch_69a2f018129c81909494450fcba71b59 |
completed | Feb. 28, 2026, 1:39 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.