Triple
T7989670
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Los Angeles Metro D Line |
E185768
|
entity |
| Predicate | corridorCharacteristic |
P26881
|
FINISHED |
| Object | high-density urban 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: high-density urban corridor | Statement: [Los Angeles Metro D Line, corridorCharacteristic, high-density urban corridor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: corridorCharacteristic Context triple: [Los Angeles Metro D Line, corridorCharacteristic, high-density urban corridor]
-
A.
corridorType
chosen
Indicates the specific kind or classification of a corridor associated with an entity or location.
-
B.
corridorOrientation
Indicates the directional alignment or bearing of a corridor relative to a reference frame or coordinate system.
-
C.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
-
D.
lengthOfCorridors
Indicates the measured extent or distance of corridors within a given space or structure.
-
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_69ca829a2cfc819083d591d58ec04075 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c4f98808190879113ad4af9bb4d |
completed | March 31, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:16 p.m.