Triple
T25289131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jean Conservation Camp |
E634030
|
entity |
| Predicate | workProgram |
P87760
|
FINISHED |
| Object | litter cleanup |
—
|
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: litter cleanup | Statement: [Jean Conservation Camp, workProgram, litter cleanup]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: workProgram Context triple: [Jean Conservation Camp, workProgram, litter cleanup]
-
A.
worksOnProgram
Indicates that an entity is actively involved in contributing effort or performing tasks on a particular program.
-
B.
hasWorkProgram
chosen
Indicates that an entity offers, participates in, or is associated with a specific work-related program or scheme.
-
C.
professionalProgram
Indicates that an entity is enrolled in, associated with, or part of a specialized professional education or training program.
-
D.
workFor
Indicates that one entity is employed by or performs work under the authority or direction of another entity.
-
E.
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.
- 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_69e75a9503d48190b80a005c6af0cb50 |
completed | April 21, 2026, 11:08 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 1:21 p.m.