Triple
T3513847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ozurgeti |
E74258
|
entity |
| Predicate | distanceToBlackSea |
P48447
|
FINISHED |
| Object | about 25 kilometres |
—
|
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: about 25 kilometres | Statement: [Ozurgeti, distanceToBlackSea, about 25 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBlackSea Context triple: [Ozurgeti, distanceToBlackSea, about 25 kilometres]
-
A.
distanceFromMediterranean
Indicates the measured spatial distance between a given location and the Mediterranean Sea.
-
B.
distanceToBucharest
Indicates the physical distance between a given location and the city of Bucharest.
-
C.
distanceFromKutaisi
Indicates the spatial distance measured from the location of Kutaisi to another specified place or entity.
-
D.
distanceToRussianBorder_km
Indicates the physical distance, measured in kilometers, between a given location and the nearest point on the Russian border.
-
E.
distanceFrom Tbilisi
Indicates the spatial distance between a given location or entity and the city of Tbilisi.
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc2d0bf481909d1f19a87d147b63 |
completed | March 8, 2026, 6:13 p.m. |
| PD | Predicate disambiguation | batch_69adae0e770481908528fa35eda53003 |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaed74ecc8190b74dc70ab59a3e1c |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:19 p.m.