Triple
T14284501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Striking Hour |
E354132
|
entity |
| Predicate | hasPrimaryMessage |
P85911
|
FINISHED |
| Object | Outcome depends on the weight of one’s deeds |
—
|
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: Outcome depends on the weight of one’s deeds | Statement: [The Striking Hour, hasPrimaryMessage, Outcome depends on the weight of one’s deeds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryMessage Context triple: [The Striking Hour, hasPrimaryMessage, Outcome depends on the weight of one’s deeds]
-
A.
hasPrimary
Indicates that one entity is designated as the main or most important instance (the primary) in relation to another entity.
-
B.
hasPrimarySubject
Indicates that an entity is the main or principal subject associated with another entity or resource.
-
C.
hasPrimaryCode
Indicates that an entity is associated with its main or most important identifying code among potentially multiple codes.
-
D.
hasKeyMessage
chosen
Indicates that one entity conveys, contains, or is associated with a primary or central message of another entity.
-
E.
hasPrimaryMeeting
Indicates that an entity is associated with its main or most important meeting, distinguishing it from other meetings it may have.
- 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_69d8278d25148190abf1a8c8f5f533ad |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de697d9fd08190b0cd7a6a6737ba03 |
completed | April 14, 2026, 4:21 p.m. |
| PD | Predicate disambiguation | batch_69de2a88446481909cd526da97a3b70f |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:10 a.m.