Triple
T18605592
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CTA Route 66 Chicago |
E454734
|
entity |
| Predicate | hasRouteTypeCode |
P56964
|
FINISHED |
| Object | bus |
—
|
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: bus | Statement: [CTA Route 66 Chicago, hasRouteTypeCode, bus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteTypeCode Context triple: [CTA Route 66 Chicago, hasRouteTypeCode, bus]
-
A.
hasRouteType
Indicates that there is a specific kind or category of route associated with an entity (e.g., road, rail, bus line).
-
B.
hasTypeCode
chosen
Indicates that an entity is associated with a specific type classification represented by a code.
-
C.
includesRouteType
Indicates that one entity’s set of routes contains or covers a specific type or category of route associated with another entity.
-
D.
hasMajorRouteType
Indicates that an entity is associated with a primary classification of transportation route (such as highway, rail line, or other major route type).
-
E.
hasRoute
Indicates that there exists a path or connection enabling travel or communication from one entity to another.
- 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_69d8d38bbe7c8190bdec3138e7d413c9 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e547544a248190a3465e22dfb29305 |
completed | April 19, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69e478cf5e888190a0b1074b0c6525df |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:45 a.m.