Triple
T20114973
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Day by day, dear Lord |
E490434
|
entity |
| Predicate | temporalEmphasis |
P119686
|
FINISHED |
| Object | daily life |
—
|
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: daily life | Statement: [Day by day, dear Lord, temporalEmphasis, daily life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalEmphasis Context triple: [Day by day, dear Lord, temporalEmphasis, daily life]
-
A.
temporalConnotation
chosen
Indicates a relationship where something carries, implies, or is associated with a particular sense of time, timing, or temporal context.
-
B.
temporal
Indicates a relationship that situates one event, state, or entity in time relative to another (e.g., before, after, or during).
-
C.
temporalAspect
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
D.
temporality
Indicates the time-related relationship between events or states, such as their order, duration, or simultaneity.
-
E.
temporalEffect
Indicates a relationship where one event, state, or action produces consequences or changes that occur at a later time.
- 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666e3f2288190840d1eb431ac9a1b |
completed | April 20, 2026, 5:48 p.m. |
| PD | Predicate disambiguation | batch_69e54cf788188190a46cc49c9ce7617f |
completed | April 19, 2026, 9:45 p.m. |
Created at: April 11, 2026, 11:29 p.m.