Triple
T28324844
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | orgone energy |
E717378
|
entity |
| Predicate | influencesAccordingToProponent |
P173356
|
FINISHED |
| Object | human health |
—
|
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: human health | Statement: [orgone energy, influencesAccordingToProponent, human health]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: influencesAccordingToProponent Context triple: [orgone energy, influencesAccordingToProponent, human health]
-
A.
influencesThrough
Indicates that one entity affects or alters another entity indirectly by means of an intermediate factor, channel, or mechanism.
-
B.
influenceOf
chosen
Indicates that one entity affects, shapes, or alters the state, behavior, or properties of another entity.
-
C.
incorporatesInfluence
Indicates that one entity integrates or absorbs the influence, ideas, or characteristics of another into itself.
-
D.
influencedBeliefAbout
Indicates that one entity has affected or shaped another entity’s belief or opinion regarding a particular subject or target.
-
E.
influencedIn
Indicates that one entity had an effect on or shaped another entity within a specific context, domain, or setting.
- 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_69eff6e6c3b08190ad78de6ba7f04548 |
completed | April 27, 2026, 11:53 p.m. |
| NER | Named-entity recognition | batch_69f6d0d46aec819091edf97324d793ac |
completed | May 3, 2026, 4:36 a.m. |
| PD | Predicate disambiguation | batch_69f6cfe2183481908ae4e85a59c66f69 |
completed | May 3, 2026, 4:32 a.m. |
Created at: April 28, 2026, 12:27 a.m.