Triple
T17276073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Factor Four |
E419394
|
entity |
| Predicate | hasCaseStudiesOn |
P2398
|
FINISHED |
| Object | energy-efficient buildings |
—
|
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-efficient buildings | Statement: [Factor Four, hasCaseStudiesOn, energy-efficient buildings]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCaseStudiesOn Context triple: [Factor Four, hasCaseStudiesOn, energy-efficient buildings]
-
A.
hasCaseStudy
chosen
Indicates that one entity is documented, illustrated, or analyzed by a specific case study associated with it.
-
B.
feasibilityStudiesBy
Indicates that feasibility studies are conducted or authored by a specified agent or entity.
-
C.
caseStudyNumber
Indicates the identifying number assigned to a specific case study within a collection or series.
-
D.
hasStudyModel
Indicates that an entity is associated with, or defined by, a particular study model used for analysis, simulation, or representation.
-
E.
hasScientificStudy
Indicates that there exists a scientific study that investigates, analyzes, or provides evidence about the referenced entity 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_69d886da626481908a14ce7830329a35 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e4332625c48190a25bf51543d797c3 |
completed | April 19, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69e3832c3b98819091967ac7e91ba316 |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:40 a.m.