Triple
T33193840
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sunday school teacher |
E849690
|
entity |
| Predicate | mayWorkOn |
P176169
|
FINISHED |
| Object | other days of the week |
—
|
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: other days of the week | Statement: [Sunday school teacher, mayWorkOn, other days of the week]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayWorkOn Context triple: [Sunday school teacher, mayWorkOn, other days of the week]
-
A.
mayWorkIn
Indicates that an entity is allowed or has the possibility to work in a particular place, organization, or context.
-
B.
hasWorkOn
Indicates that one entity is associated with, contributes to, or performs work on another entity (such as a project, task, or artifact).
-
C.
worksFor
Indicates that one entity is employed by or performs work on behalf of another entity, typically an organization or individual.
-
D.
worksTo
Indicates that one entity performs work or exerts effort in order to achieve, support, or contribute to another entity or outcome.
-
E.
namedForWorkOn
Indicates that an entity is named in honor of another entity specifically because of that entity’s work or contributions in a particular field or endeavor.
- 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_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
| PDg | Predicate description generation | batch_69f6dd3b335481909e24d4eb5b0269f9 |
completed | May 3, 2026, 5:29 a.m. |
Created at: May 1, 2026, 1:29 a.m.