Triple
T35680285
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belgian railway line 96 |
E1030985
|
entity |
| Predicate | borderTerminusCountry |
P93185
|
FINISHED |
| Object | France |
—
|
NE NERFINISHED |
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: France | Statement: [Belgian railway line 96, borderTerminusCountry, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: borderTerminusCountry Context triple: [Belgian railway line 96, borderTerminusCountry, France]
-
A.
hasBorderTerminusCountry
Indicates that a country serves as the endpoint or boundary limit of a border segment associated with another entity.
-
B.
borderTerminus
chosen
Indicates the endpoint location where a border between two areas or entities begins or ends.
-
C.
borderCountrySide
Indicates that one country shares a land border with the side or region of another country.
-
D.
borderingEntityCountry
Indicates that one country shares a land or maritime boundary with another country.
-
E.
nearestInternationalBorderCrossingCountry
Indicates the country in which the closest international border crossing point to a given location is situated.
- 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_69f76e0bb6608190ad3a1880be54a17d |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffacdf9f5c8190baef0245edfe87fc |
completed | May 9, 2026, 9:53 p.m. |
| PD | Predicate disambiguation | batch_69ffac5e86e08190a1e6da0840a237ad |
completed | May 9, 2026, 9:51 p.m. |
Created at: May 3, 2026, 4:05 p.m.