Triple
T10185978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A39 motorway (France) |
E236908
|
entity |
| Predicate | maintainedBy |
P86
|
FINISHED |
| Object | APRR |
E244508
|
NE 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: APRR | Statement: [A39 motorway (France), maintainedBy, APRR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: APRR Context triple: [A39 motorway (France), maintainedBy, APRR]
-
A.
APRR
chosen
APRR is a major French motorway concession and operating company responsible for managing and maintaining a large portion of France’s autoroute network.
-
B.
APRU
APRU (Association of Pacific Rim Universities) is a consortium of leading research universities around the Pacific Rim that collaborates on education, research, and policy initiatives.
-
C.
APRIN
APRIN is a Japanese organization focused on promoting research integrity and ethical conduct in academic and scientific communities.
-
D.
APRALO
APRALO is the Asia Pacific Regional At-Large Organization within ICANN that represents and coordinates the interests of individual Internet users in the Asia-Pacific region.
-
E.
APAS
APAS is a type of androgynous docking mechanism developed for spacecraft to enable compatible, flexible docking between different vehicles.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca84d7260c8190bfbec36762943f37 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cded790b488190b1ed4645554873cd |
completed | April 2, 2026, 4:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d317a4d99c8190941322d3de2998f5 |
completed | April 6, 2026, 2:17 a.m. |
Created at: March 30, 2026, 9:12 p.m.