Triple
T28021064
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Crosstown Local |
E707687
|
entity |
| Predicate | hasRouteSymbolColor |
P69958
|
FINISHED |
| Object | light green circle with white G |
—
|
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: light green circle with white G | Statement: [Crosstown Local, hasRouteSymbolColor, light green circle with white G]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRouteSymbolColor Context triple: [Crosstown Local, hasRouteSymbolColor, light green circle with white G]
-
A.
hasRouteColorStandard
Indicates that a route is associated with a standardized color designation used for identification or classification.
-
B.
hasColorSymbol
Indicates that one entity is associated with another entity that serves as its representative or symbolic color.
-
C.
hasColorOnRouteMap
chosen
Indicates that a specific color is used to represent an entity (such as a route or line) on a route map.
-
D.
hasRouteAlignment
Indicates that there is a defined spatial or geometric alignment associated with a route or pathway.
-
E.
hasRouteNumberingRole
Indicates that an entity participates in the assignment, management, or designation of route numbers for a transportation route or network.
- 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_69ef96baf3a881909a2b63844185dddd |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: April 27, 2026, 8:10 p.m.