Triple
T7539594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samos International Airport |
E178238
|
entity |
| Predicate | hasChallengingTerrainNearby |
P43110
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Samos International Airport, hasChallengingTerrainNearby, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChallengingTerrainNearby Context triple: [Samos International Airport, hasChallengingTerrainNearby, true]
-
A.
hasRockyTerrain
Indicates that the subject possesses or is characterized by rough, uneven, or rock-covered ground or surface conditions.
-
B.
hasMountainousTerrain
Indicates that a location or area possesses predominantly mountainous physical terrain or landscape features.
-
C.
hasTrailDifficulty
Indicates the level of challenge or effort required to traverse a particular trail or route.
-
D.
hasAdvancedTerrain
chosen
Indicates that an entity possesses or is associated with terrain featuring complex, challenging, or enhanced physical characteristics beyond standard ground conditions.
-
E.
hasMountainPassNearby
Indicates that a mountain pass is located in close proximity to the referenced place or feature.
- 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_69c69f2be3888190a6667a27f8f195e9 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f87280f0819097d4ffc2e1b62cf8 |
completed | March 27, 2026, 9:36 p.m. |
| PD | Predicate disambiguation | batch_69c6f4d8eedc81908c1ae421e0e63798 |
completed | March 27, 2026, 9:21 p.m. |
Created at: March 27, 2026, 3:48 p.m.