Triple
T13874796
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | State Route 79 |
E333551
|
entity |
| Predicate | hasSegmentCharacter |
P2563
|
FINISHED |
| Object | two-lane rural highway |
—
|
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: two-lane rural highway | Statement: [State Route 79, hasSegmentCharacter, two-lane rural highway]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSegmentCharacter Context triple: [State Route 79, hasSegmentCharacter, two-lane rural highway]
-
A.
hasComponentCharacter
Indicates that one entity includes another entity as a constituent character or symbolic component.
-
B.
hasRegularSegment
Indicates that an entity includes or is associated with a segment that occurs in a consistent, repeating, or standard pattern.
-
C.
hasSegmentOn
Indicates that one entity includes or occupies a specific segment or portion on another entity (such as a line, path, or sequence).
-
D.
hasSegmentType
chosen
Indicates that an entity is associated with, or classified by, a particular type or category of segment within a larger structure or sequence.
-
E.
hasSeparator
Indicates that one entity includes, uses, or is divided by another entity that serves as a separator or delimiting element.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de23a101488190bd790b28033d38b9 |
completed | April 14, 2026, 11:23 a.m. |
| PD | Predicate disambiguation | batch_69de05972f3881909977b4c843984f88 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:14 p.m.