Triple
T30714771
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NM-02 trains |
E781992
|
entity |
| Predicate | routeAssignment |
P170490
|
FINISHED |
| Object | Line 3 Indios Verdes–Universidad |
—
|
NE NERFINISHED |
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: Line 3 Indios Verdes–Universidad | Statement: [NM-02 trains, routeAssignment, Line 3 Indios Verdes–Universidad]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: routeAssignment Context triple: [NM-02 trains, routeAssignment, Line 3 Indios Verdes–Universidad]
-
A.
laneAssignment
Indicates the specific lane or set of lanes that an entity (such as a vehicle or participant) is assigned to use within a multi-lane context.
-
B.
routeSetting
Indicates that one entity configures or defines the path or course to be followed by another entity (such as a vehicle, signal, or data flow).
-
C.
routeRole
Indicates the specific functional role or purpose that an entity has within a particular route or path.
-
D.
route
Indicates that one entity serves as a path or course used to travel or move between locations associated with another entity.
-
E.
routeArea
Indicates that an area is associated with, covered by, or traversed by a particular route.
- 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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69063edbc81909e7735954aabee0b |
completed | May 3, 2026, 12:01 a.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68f6584a88190a8c4d95c0c84bee9 |
completed | May 2, 2026, 11:57 p.m. |
Created at: April 29, 2026, 8:35 p.m.