Triple
T15201470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kastani Beach |
E363277
|
entity |
| Predicate | distanceFromSkopelosTown |
P117100
|
FINISHED |
| Object | approximately 15 km by road |
—
|
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 15 km by road | Statement: [Kastani Beach, distanceFromSkopelosTown, approximately 15 km by road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceFromSkopelosTown Context triple: [Kastani Beach, distanceFromSkopelosTown, approximately 15 km by road]
-
A.
distanceFromMykonosTown
Indicates the spatial distance separating a given place or object from Mykonos Town.
-
B.
distanceFromSamosTownKilometers
Indicates the distance, measured in kilometers, between a given place and Samos Town.
-
C.
distanceToNafplio
Indicates the spatial distance between a given entity’s location and the location of Nafplio.
-
D.
distanceFromHeraklion
Indicates the spatial distance between a given location and the city of Heraklion.
-
E.
distanceToLesbos
Indicates the spatial distance between a given entity and the location of Lesbos.
- 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b588b88190a88e91d521acbdfe |
completed | April 15, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69deb97ee9d881908711dbe12a55283c |
completed | April 14, 2026, 10:02 p.m. |
| PDg | Predicate description generation | batch_69dec72059c08190a34f513a00185b08 |
completed | April 14, 2026, 11 p.m. |
Created at: April 10, 2026, 3:10 a.m.