Triple
T1924080
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Science: Good, Bad and Bogus |
E40188
|
entity |
| Predicate | positionOnFringeTheories |
P25536
|
FINISHED |
| Object | critical |
—
|
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: critical | Statement: [Science: Good, Bad and Bogus, positionOnFringeTheories, critical]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionOnFringeTheories Context triple: [Science: Good, Bad and Bogus, positionOnFringeTheories, critical]
-
A.
occursInTheory
Indicates that an event, concept, or phenomenon is situated, described, or analyzed within a particular theoretical framework or theory.
-
B.
contradictedTheory
Indicates that one entity has presented evidence, arguments, or findings that oppose, challenge, or invalidate the theory proposed by another entity.
-
C.
subtheory
Indicates that one theory is a component, specialization, or restricted part of another, more general theory.
-
D.
theorized
Indicates that one entity has proposed or developed a theoretical explanation or hypothesis about another entity or phenomenon.
-
E.
hasTheoreticalStatus
chosen
Indicates that something possesses a particular theoretical standing, classification, or role within a conceptual or theoretical framework.
- 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_69a8864298748190a2f2fd34f7ef8d77 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb2359ca0819082b514a34c469b21 |
completed | March 7, 2026, 5:05 a.m. |
| PD | Predicate disambiguation | batch_69abafed2ab481908920334e77b1021b |
completed | March 7, 2026, 4:56 a.m. |
Created at: March 4, 2026, 7:35 p.m.