Triple
T13892418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ravens paradox |
E334006
|
entity |
| Predicate | involvesExample |
P1256
|
FINISHED |
| Object | observation of a black raven |
—
|
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: observation of a black raven | Statement: [Ravens paradox, involvesExample, observation of a black raven]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvesExample Context triple: [Ravens paradox, involvesExample, observation of a black raven]
-
A.
involves
chosen
Indicates that an entity participates in, is a part of, or is implicated within a particular event, process, or relationship.
-
B.
includesExamplesSuchAs
Indicates that one entity provides specific instances or samples that illustrate or clarify another entity.
-
C.
usedAsExampleIn
Indicates that one entity is cited or presented as an illustrative example within another entity, such as a text, discussion, or explanation.
-
D.
definitionInvolves
Indicates that the meaning or explanation of one concept necessarily includes or depends on another concept.
-
E.
mayBeInvolvedIn
Indicates that an entity has a possible, but not certain, participation or role in a particular event, activity, or situation.
- 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_69d81c5dd2d48190b7a5fc1e009de936 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a537d4819093c2bae2a244816a |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69dd464b1ab48190ae50bfc902bf6ef7 |
completed | April 13, 2026, 7:38 p.m. |
Created at: April 9, 2026, 10:15 p.m.