Triple
T34558952
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dapitan Street |
E887284
|
entity |
| Predicate | hasTimePattern |
P79788
|
FINISHED |
| Object | busy during school year |
—
|
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: busy during school year | Statement: [Dapitan Street, hasTimePattern, busy during school year]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTimePattern Context triple: [Dapitan Street, hasTimePattern, busy during school year]
-
A.
hasTimeComponent
Indicates that something includes, is associated with, or is characterized by a specific temporal aspect or time-related element.
-
B.
hasTimeOptions
Indicates that an entity is associated with one or more selectable time choices or configurations.
-
C.
hasPattern
Indicates that one entity exhibits, follows, or is characterized by a specific recurring form, structure, or design defined by another entity.
-
D.
hasTimeIndication
chosen
Indicates that something includes, specifies, or is associated with a particular time-related indication (such as a timestamp, time period, or temporal marker).
-
E.
hasDayCountPattern
Indicates a relationship where something follows or is associated with a specific pattern in the number or arrangement of days.
- 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_69f349d0c4d881908dd0950f5eb9ec0a |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69fd974d75e08190af46b1d608769f3b |
completed | May 8, 2026, 7:57 a.m. |
| PD | Predicate disambiguation | batch_69fd94ff792c8190bedf4a639d3da809 |
completed | May 8, 2026, 7:47 a.m. |
Created at: May 1, 2026, 2:02 a.m.