Triple
T1526453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Interstate 75 near Lake City |
E32345
|
entity |
| Predicate | connectsToCorridor |
P5520
|
FINISHED |
| Object | Interstate 10 east–west corridor |
—
|
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: Interstate 10 east–west corridor | Statement: [Interstate 75 near Lake City, connectsToCorridor, Interstate 10 east–west corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsToCorridor Context triple: [Interstate 75 near Lake City, connectsToCorridor, Interstate 10 east–west corridor]
-
A.
hasCorridor
chosen
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
B.
corridorType
Indicates the specific kind or classification of a corridor associated with an entity or location.
-
C.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another entity.
-
D.
hasServiceOnCorridor
Indicates that a service operates along, or is provided on, a specific corridor or route.
-
E.
numberOfCorridors
Indicates the total count of corridors associated with or contained within a given entity or structure.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a933ddc5a881909cdf503f2bc29bd4 |
completed | March 5, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69a907ae8f688190ad9000ea1e018585 |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.