Triple
T14927195
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sebastianism |
E372162
|
entity |
| Predicate | hasTemporalExpectation |
P116692
|
FINISHED |
| Object | return at an unknown future time |
—
|
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: return at an unknown future time | Statement: [Sebastianism, hasTemporalExpectation, return at an unknown future time]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTemporalExpectation Context triple: [Sebastianism, hasTemporalExpectation, return at an unknown future time]
-
A.
hasTemporalBehavior
Indicates that an entity exhibits a particular pattern, characteristic, or change in behavior over time.
-
B.
hasTemporalUse
Indicates that something is used, applicable, or valid only during a specific time or temporal interval.
-
C.
hasTemporalResolution
Indicates that one entity specifies the level of temporal detail or granularity at which another entity’s data, observation, or process is measured or represented.
-
D.
hasTemporalRole
Indicates that an entity participates in a role or function that is defined, constrained, or characterized by a specific time or temporal context.
-
E.
temporalAwareness
Indicates an entity’s ability to perceive, understand, or track the passage and ordering of time-related events.
- 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_69d85cc9da0c81908d583ca3f63a3908 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded633da0c8190b39f606212e48e71 |
completed | April 15, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69de9a52ba988190a26e268b4ea083ea |
completed | April 14, 2026, 7:49 p.m. |
| PDg | Predicate description generation | batch_69deb1a4d8dc8190a4c0841c20f2875f |
completed | April 14, 2026, 9:29 p.m. |
Created at: April 10, 2026, 2:35 a.m.