Triple
T13674079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North–south Interstate Highways |
E327826
|
entity |
| Predicate | typicalNumberingScheme |
P3378
|
FINISHED |
| Object | odd route numbers |
—
|
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: odd route numbers | Statement: [North–south Interstate Highways, typicalNumberingScheme, odd route numbers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberingScheme Context triple: [North–south Interstate Highways, typicalNumberingScheme, odd route numbers]
-
A.
standardNumberingScheme
Indicates that there is a specific, commonly accepted numbering system or convention being applied to identify or order the related entities.
-
B.
numberingType
chosen
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
C.
categoryNumbering
Indicates that items within a category are assigned an ordered or structured numbering scheme that defines their position or sequence in that category.
-
D.
legalNumbering
Indicates that an entity has an officially assigned legal or regulatory identification number.
-
E.
numberingReason
Indicates the rationale or basis for assigning a particular number or numbering scheme to something.
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65aab348190a6611f5765f8392d |
completed | April 12, 2026, 4:20 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:53 p.m.