Triple
T30905918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Insula Șerpilor |
E787299
|
entity |
| Predicate | distanceToUkrainianCoast |
P129538
|
FINISHED |
| Object | about 37 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 37 kilometres | Statement: [Insula Șerpilor, distanceToUkrainianCoast, about 37 kilometres]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToUkrainianCoast Context triple: [Insula Șerpilor, distanceToUkrainianCoast, about 37 kilometres]
-
A.
distanceToUkraineBorder
chosen
Indicates the measured distance between a given location or entity and the border of Ukraine.
-
B.
distanceFromKyiv
Indicates the spatial distance between a given entity’s location and the city of Kyiv.
-
C.
distanceToRomanianCoast
Indicates the measured or calculated distance between a given location and the coastline of Romania.
-
D.
distanceToBlackSea
Indicates the measured spatial distance between a given entity and the Black Sea.
-
E.
distanceToDonetsk
Indicates the spatial distance between a given entity and the location of Donetsk.
- 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_69f224bcbcb48190836df847424e4057 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_6a0174e8b5b481908bf0c6d3d5b0f3b6 |
completed | May 11, 2026, 6:19 a.m. |
| PD | Predicate disambiguation | batch_6a01748d65248190ac3d9adfa9d0b274 |
completed | May 11, 2026, 6:17 a.m. |
Created at: April 29, 2026, 8:50 p.m.