Triple
T25756112
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delmarva Power |
E648600
|
entity |
| Predicate | hasCustomerPrograms |
P171734
|
FINISHED |
| Object | energy efficiency 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: energy efficiency programs | Statement: [Delmarva Power, hasCustomerPrograms, energy efficiency programs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomerPrograms Context triple: [Delmarva Power, hasCustomerPrograms, energy efficiency programs]
-
A.
hasAwardProgram
Indicates that an entity maintains or offers a formal award or recognition program.
-
B.
hasMembershipProgram
Indicates that an entity offers or participates in a structured membership program, typically providing special access, benefits, or services to enrolled members.
-
C.
hasCoopPrograms
Indicates that an entity offers or participates in cooperative education programs in partnership with other organizations or institutions.
-
D.
hasPartnershipProgram
Indicates that an entity maintains a formal partnership program through which it establishes and manages collaborative relationships with other entities.
-
E.
offersProgramsIn
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
- F. None of above. chosen
Provenance (4 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_69e7ab314d788190b3abe19e114080e1 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
| PDg | Predicate description generation | batch_69f6a28b8ea881908733485374771c51 |
completed | May 3, 2026, 1:19 a.m. |
Created at: April 22, 2026, 4:40 a.m.