Triple
T20805961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rebecka |
E512154
|
entity |
| Predicate | meaningViaRebecca |
P141895
|
FINISHED |
| Object | to tie |
—
|
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: to tie | Statement: [Rebecka, meaningViaRebecca, to tie]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: meaningViaRebecca Context triple: [Rebecka, meaningViaRebecca, to tie]
-
A.
meaningViaLeonard
Indicates that something has a particular meaning or interpretation as conveyed or defined by Leonard.
-
B.
meaningViaAndrzej
Indicates that something’s meaning or interpretation is conveyed, mediated, or understood specifically through Andrzej.
-
C.
meaningViaPatricia
Indicates that something’s meaning, interpretation, or understanding is conveyed, mediated, or determined through an intermediary named Patricia.
-
D.
meaningViaJoshua
Indicates that something is understood, interpreted, or conveyed through the perspective, explanation, or mediation of Joshua.
-
E.
meaningViaMargaret
Indicates that one entity’s meaning, interpretation, or significance is mediated, conveyed, or established through an intermediary entity named Margaret.
- F. None of above. chosen
Provenance (4 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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2cf1cbc819092d92625dfb107d0 |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
| PDg | Predicate description generation | batch_69e5d53c4d6881909b4d0a716fa5ed4a |
completed | April 20, 2026, 7:26 a.m. |
Created at: April 16, 2026, 12:40 p.m.