Triple
T845369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L train |
E18264
|
entity |
| Predicate | routeDescription |
P20574
|
FINISHED |
| Object | Runs crosstown along 14th Street in Manhattan |
—
|
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: Runs crosstown along 14th Street in Manhattan | Statement: [L train, routeDescription, Runs crosstown along 14th Street in Manhattan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeDescription Context triple: [L train, routeDescription, Runs crosstown along 14th Street in Manhattan]
-
A.
route
Indicates that one entity serves as a path or course used to travel or move between locations associated with another entity.
-
B.
routeCategory
Indicates the classification or type assigned to a route within a transportation or path network.
-
C.
routeVia
Indicates that a connection, path, or communication between two points is established or carried out through an intermediate location, node, or channel.
-
D.
routeNumber
Indicates the specific identifying number assigned to a route within a transportation or delivery network.
-
E.
notableRouteType
Indicates that a route is particularly significant or well-known for a specific type or category (e.g., scenic, historic, commercial).
- 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_69a4938b04208190b82e1df6b572c548 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac0a91e48190b4349ae8bb67fd90 |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7f396c8190aa8b8dfbe0b4f732 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4893e481908632102d240466dc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.