Triple
T2247124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A86 autoroute |
E49528
|
entity |
| Predicate | tunnelSectionType |
P29550
|
FINISHED |
| Object | double-deck tunnel |
—
|
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: double-deck tunnel | Statement: [A86 autoroute, tunnelSectionType, double-deck tunnel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tunnelSectionType Context triple: [A86 autoroute, tunnelSectionType, double-deck tunnel]
-
A.
tunnelType
chosen
Indicates the specific kind or classification of a tunnel associated with an entity.
-
B.
SeikanTunnelType
Indicates that one entity is classified as a specific type or category of Seikan Tunnel.
-
C.
stratotypeSection
Indicates the reference rock section formally designated as the standard or type example for a particular stratigraphic unit or boundary.
-
D.
guidewayType
Indicates the specific kind or classification of guideway used in a transportation or movement system.
-
E.
tunnelCircumference
Indicates the circular distance around the inner boundary of a tunnel’s cross-section.
- 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_69a88aa979788190ad6500f1d8eee2fc |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc0ec46b08190ae12de8b255eb71d |
completed | March 7, 2026, 6:08 a.m. |
| PD | Predicate disambiguation | batch_69abbdb160248190aa75b38f11ad8602 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.