Triple
T35968013
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Akshobhya |
E1040196
|
entity |
| Predicate | correspondsToSense |
P29818
|
FINISHED |
| Object | ear (in some systems) |
—
|
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: ear (in some systems) | Statement: [Akshobhya, correspondsToSense, ear (in some systems)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: correspondsToSense Context triple: [Akshobhya, correspondsToSense, ear (in some systems)]
-
A.
hasSense
chosen
Indicates that an entity possesses or is associated with a particular sensory perception, meaning, or interpretation.
-
B.
correspondsWith
Indicates that two entities are in mutual alignment or agreement, such that one matches, parallels, or is equivalent to the other in a specified respect.
-
C.
correspondsToLatinWord
Indicates that one element is the equivalent or matching term of another element in Latin.
-
D.
containsCorrespondenceWith
Indicates that one entity includes or holds correspondence (such as messages or communications) that is associated with or exchanged with another entity.
-
E.
refersSpecificallyTo
Indicates that one entity makes an explicit, precise reference to another particular entity, distinguishing it from more general or ambiguous references.
- 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_69f76e26b21081909fd9ffb3aff6c77a |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:07 p.m.