Triple
T4566126
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dipsea Trail segments |
E121912
|
entity |
| Predicate | seasonalUsePattern |
P955
|
FINISHED |
| Object | year-round use |
—
|
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: year-round use | Statement: [Dipsea Trail segments, seasonalUsePattern, year-round use]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonalUsePattern Context triple: [Dipsea Trail segments, seasonalUsePattern, year-round use]
-
A.
hasSeasonalPattern
chosen
Indicates that the occurrence, intensity, or characteristics of something regularly vary according to a recurring seasonal cycle.
-
B.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
C.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
D.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
-
E.
basedOnSeason
Indicates that something is determined, influenced, or derived according to a particular season or time of year.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589cde9081909b84186d700fc463 |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd52254c648190a5144cfe8fa7e409 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.