Triple
T5206143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Dreamer |
E117514
|
entity |
| Predicate | temporalSettingOfVision |
P29111
|
FINISHED |
| Object | night |
—
|
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: night | Statement: [the Dreamer, temporalSettingOfVision, night]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: temporalSettingOfVision Context triple: [the Dreamer, temporalSettingOfVision, night]
-
A.
temporalAspect
chosen
Indicates the time-related characteristics or phase (such as duration, frequency, or temporal status) associated with an event or relationship.
-
B.
locationOfVision
Indicates the place or setting where a vision or visual experience occurs or is perceived.
-
C.
temporality
Indicates the time-related relationship between events or states, such as their order, duration, or simultaneity.
-
D.
timePerspective
Indicates how an entity conceptually relates to or orients itself toward time, such as focusing on past, present, or future.
-
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_69bd4463dd3c81909966123f20b79d57 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd7a490338819080481df79d3aae01 |
completed | March 20, 2026, 4:48 p.m. |
| PD | Predicate disambiguation | batch_69bd77bb4e8c819094b5ac7cf61512f9 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:47 p.m.