Triple
T7410579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Experience (essay) |
E170990
|
entity |
| Predicate | exploresRelationBetween |
P63064
|
FINISHED |
| Object | experience and reality |
—
|
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: experience and reality | Statement: [Experience (essay), exploresRelationBetween, experience and reality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exploresRelationBetween Context triple: [Experience (essay), exploresRelationBetween, experience and reality]
-
A.
exploresRelationship
chosen
Indicates that one entity actively investigates, examines, or probes the nature, dynamics, or implications of its relationship with another entity.
-
B.
relatedStudy
Indicates that one study is connected or relevant to another study, typically through shared topics, methods, or findings.
-
C.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
-
D.
exploresContrastBetween
Indicates a relationship in which one entity examines, highlights, or analyzes the differences or oppositions between two or more entities, ideas, or situations.
-
E.
semanticRelation
Indicates a general meaning-based connection between two entities, such as similarity, implication, or conceptual association.
- 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_69c68a618bdc81908d8018edadecd1a4 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f29ebea48190be96c6bc1e6406fb |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0345040819094c5756dfa487faf |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:11 p.m.