Triple
T6257091
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 110 (Florida) |
E140195
|
entity |
| Predicate | hasExitNumberingScheme |
P34119
|
FINISHED |
| Object | sequential exit numbering |
—
|
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: sequential exit numbering | Statement: [Interstate 110 (Florida), hasExitNumberingScheme, sequential exit numbering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasExitNumberingScheme Context triple: [Interstate 110 (Florida), hasExitNumberingScheme, sequential exit numbering]
-
A.
hasRouteNumberingScheme
Indicates that one entity uses or is assigned a particular system or scheme for numbering its routes.
-
B.
hasJunctionNumberingScheme
chosen
Indicates the specific system or method used to assign numbers to junctions within a network (such as roads or railways).
-
C.
standardNumberingScheme
Indicates that there is a specific, commonly accepted numbering system or convention being applied to identify or order the related entities.
-
D.
numberingType
Indicates the scheme or style used to assign sequential numbers or labels within an ordered set.
-
E.
hasCategoryNumbering
Indicates that an entity is assigned or associated with a specific category-based numbering or index within a classification system.
- 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_69c008c95c5c819084bd3dd56133d84d |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06366baa481908d59428cceabbe46 |
completed | March 22, 2026, 9:47 p.m. |
| PD | Predicate disambiguation | batch_69c05605566c81908e197f5accd072d2 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:24 p.m.