Triple
T23454041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Austria |
E567867
|
entity |
| Predicate | borderLengthWithHungary_km |
P152346
|
FINISHED |
| Object | about 366 |
—
|
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 366 | Statement: [Austria, borderLengthWithHungary_km, about 366]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderLengthWithHungary_km Context triple: [Austria, borderLengthWithHungary_km, about 366]
-
A.
totalLandBorderLength_km
Indicates the total length, in kilometers, of all land borders that an entity shares with neighboring entities.
-
B.
shareLandBorderLengthApproxKm
Indicates that two entities share a land border whose length is approximately the given number of kilometers.
-
C.
borderLengthWithFinland
Indicates the total length of the land or maritime border that an entity shares with Finland.
-
D.
longestLandBorderWith
Indicates that two entities share a land border and that this border is the longest land border for at least one of the entities.
-
E.
borderingCountryAcrossDanube
Indicates that one country shares a border with another country specifically across the Danube River.
- 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_69e2458b4c888190b1d7998f9862a558 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1a695fed08190bfa160e69200546d |
completed | April 29, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69f06201d33481909b5fd7b92d03e658 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f07cbbd7488190ab3c8ae7d0fb68bf |
completed | April 28, 2026, 9:24 a.m. |
Created at: April 17, 2026, 5:53 p.m.