Triple
T33193839
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunday school teacher |
E849690
|
entity |
| Predicate | typicallyWorksOn |
P206380
|
FINISHED |
| Object | Sunday |
—
|
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: Sunday | Statement: [Sunday school teacher, typicallyWorksOn, Sunday]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicallyWorksOn Context triple: [Sunday school teacher, typicallyWorksOn, Sunday]
-
A.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
B.
mayWorkOn
Indicates that an entity is permitted or allowed to perform work on another entity.
-
C.
worksOnIssue
Indicates that an entity (typically a person or team) is actively engaged in addressing, resolving, or contributing work toward a specific issue.
-
D.
worksOnProgram
Indicates that an entity is actively involved in contributing effort or performing tasks on a particular program.
-
E.
worksWith
Indicates that two entities collaborate or perform tasks together in a shared work-related context.
- 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_69f3495e0f108190a6a7006f79f9c2c3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c7fb9f88190b384b1b68200aef0 |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 1:29 a.m.