Triple
T34290942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Île d’Ogoz |
E879884
|
entity |
| Predicate | hasSeasonalAccessibility |
P15928
|
FINISHED |
| Object | more easily accessible in summer |
—
|
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: more easily accessible in summer | Statement: [Île d’Ogoz, hasSeasonalAccessibility, more easily accessible in summer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalAccessibility Context triple: [Île d’Ogoz, hasSeasonalAccessibility, more easily accessible in summer]
-
A.
hasSeasonalStatus
chosen
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
-
B.
hasSeasonalEvents
Indicates that an entity organizes or experiences events that occur only during specific seasons or times of the year.
-
C.
hasSeasonalHighlight
Indicates that something features a notable or emphasized aspect during a particular season or time of year.
-
D.
accessibleYearRound
Indicates that the subject can be accessed or used during all seasons of the year without interruption.
-
E.
hasSeasonalFacility
Indicates that an entity provides a facility or service that operates only during specific seasons or times of the 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_69f349b6df1c81908e5e5b6c2ab6409b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffbb1c5bf88190a0bf791213045885 |
completed | May 9, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69ffba0ab0f881908f84ef81f7a1bfe8 |
completed | May 9, 2026, 10:49 p.m. |
Created at: May 1, 2026, 1:57 a.m.