Triple
T16419496
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vassiliki Beach |
E398776
|
entity |
| Predicate | distanceFromLefkadaTown |
P123360
|
FINISHED |
| Object | approximately 38 km |
—
|
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: approximately 38 km | Statement: [Vassiliki Beach, distanceFromLefkadaTown, approximately 38 km]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromLefkadaTown Context triple: [Vassiliki Beach, distanceFromLefkadaTown, approximately 38 km]
-
A.
distanceFromSkopelosTown
Indicates the spatial distance separating a given place or object from Skopelos Town.
-
B.
distanceFromSkopelosTown_km
Indicates the distance, measured in kilometers, between an entity and Skopelos Town.
-
C.
distanceFromMykonosTown
Indicates the spatial distance separating a given place or object from Mykonos Town.
-
D.
distanceFromSamosTownKilometers
Indicates the distance, measured in kilometers, between a given place and Samos Town.
-
E.
distanceFromHeraklion
Indicates the spatial distance between a given location and the city of Heraklion.
- 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_69d87f2b9024819085c20e52de95d583 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e328f5c1bc8190a679f35bd6c0bc97 |
completed | April 18, 2026, 6:47 a.m. |
| PD | Predicate disambiguation | batch_69e226fe1dd08190865c181721f8c348 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.