Triple
T37952917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CFL network |
E946789
|
entity |
| Predicate | hasCrossBorderServiceTo |
P80566
|
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: [CFL network, hasCrossBorderServiceTo, France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrossBorderServiceTo Context triple: [CFL network, hasCrossBorderServiceTo, France]
-
A.
servesCrossBorderArea
Indicates that a service, activity, or function extends beyond a single jurisdiction and operates across national or regional borders.
-
B.
hasCrossBorderCenter
Indicates that an entity operates or is associated with a center whose activities, services, or scope extend across national borders.
-
C.
hasCrossBorderTrade
Indicates that there is trade or commercial exchange occurring between entities located in different countries or jurisdictions.
-
D.
isCrossBorder
Indicates that the relationship or action involves entities located in or spanning across different national or jurisdictional boundaries.
-
E.
hasCrossBorderInteraction
chosen
Indicates that there is an interaction, activity, or relationship occurring between entities located in different countries or jurisdictions.
- 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_69f76ef64cf08190ad3e1114b62aac67 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fd76d1e5208190a6f26651492d1e3c |
completed | May 8, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69fd702a226c81908edfda00f4be4130 |
completed | May 8, 2026, 5:10 a.m. |
Created at: May 3, 2026, 4:20 p.m.