Triple
T784990
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 35E (Texas) |
E16581
|
entity |
| Predicate | hasSuffixedRoute |
P19596
|
FINISHED |
| Object | E |
—
|
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: E | Statement: [Interstate 35E (Texas), hasSuffixedRoute, E]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSuffixedRoute Context triple: [Interstate 35E (Texas), hasSuffixedRoute, E]
-
A.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
-
B.
hasNotableRoute
Indicates that an entity (such as a transportation service or pathway) includes or is associated with a route that is considered significant, well-known, or otherwise noteworthy.
-
C.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
D.
auxiliaryRoutePattern
Indicates that one route serves as an auxiliary or supplemental path that follows or branches from a primary route according to a specific pattern or configuration.
-
E.
followsRouteOf
Indicates that one entity travels along the same path or route that another entity takes or has taken.
- F. None of above. chosen
Provenance (4 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a76b0d6c8190a09b1a0bd4a6eeec |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a67e69288190b3dc278c5bd94155 |
completed | March 1, 2026, 8:50 p.m. |
Created at: March 1, 2026, 7:37 p.m.