Triple
T31943864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | V_tb |
E815594
|
entity |
| Predicate | belongsToColumn |
P197827
|
FINISHED |
| Object | third column of CKM matrix |
—
|
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: third column of CKM matrix | Statement: [V_tb, belongsToColumn, third column of CKM matrix]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToColumn Context triple: [V_tb, belongsToColumn, third column of CKM matrix]
-
A.
belongsToMode
Indicates that something is associated with, or is a member of, a particular mode or operational state.
-
B.
belongsToPattern
Indicates that something is a component, instance, or member of a specified pattern or structured template.
-
C.
belongsToUN
Indicates that an entity is a member of, or formally affiliated with, the United Nations.
-
D.
belongsToUnion
Indicates that an entity is a member of, or affiliated with, a specific union organization.
-
E.
belongsToVersion
Indicates that something is associated with, or is a component of, a specific version of an entity or artifact.
- 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69feafa1ba0081909013800b85a9f613 |
completed | May 9, 2026, 3:53 a.m. |
| PD | Predicate disambiguation | batch_69feae58d62c81909d031f3df8992883 |
completed | May 9, 2026, 3:47 a.m. |
| PDg | Predicate description generation | batch_69feafa0acd881908bb6c01635b5537a |
completed | May 9, 2026, 3:53 a.m. |
Created at: May 1, 2026, 12:06 a.m.