Triple
T33125795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A Prayer |
E847718
|
entity |
| Predicate | copyrightStatusInMostCountries |
P120728
|
FINISHED |
| Object | public domain |
—
|
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: public domain | Statement: [A Prayer, copyrightStatusInMostCountries, public domain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: copyrightStatusInMostCountries Context triple: [A Prayer, copyrightStatusInMostCountries, public domain]
-
A.
copyrightStatus
Indicates the legal protection state of a work, specifying whether and how it is covered by copyright.
-
B.
legalStatusInManyCountries
Indicates that the subject has a particular legal classification or standing that is recognized across numerous countries.
-
C.
copyrightModel
Indicates that one entity serves as the copyright or licensing model that governs the use, distribution, or protection of another entity.
-
D.
hasLegalDepositRightFor
Indicates that an entity holds the legal right to receive, collect, or claim deposited materials (such as publications or documents) from another entity under legal deposit regulations.
-
E.
legalStatusInMostCountries
chosen
Indicates the typical legal classification or treatment of something across the majority of countries.
- 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_69f349588f088190b7c9588860f72033 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6db6af1d88190989810182354d60f |
completed | May 3, 2026, 5:21 a.m. |
| PD | Predicate disambiguation | batch_69f6d82d068c8190940a3200ed760e38 |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:27 a.m.