Triple
T3878700
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blue Line (Los Angeles Metro) |
E92567
|
entity |
| Predicate | streetRunningSections |
P52097
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Blue Line (Los Angeles Metro), streetRunningSections, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: streetRunningSections Context triple: [Blue Line (Los Angeles Metro), streetRunningSections, yes]
-
A.
streetSectionOf
Indicates that one street segment or portion belongs to, is contained within, or forms part of a larger street or roadway.
-
B.
hasStreetRunningTracks
Indicates that a location or area includes street-level tracks used for running or jogging.
-
C.
tracksSector
Indicates that one entity monitors, follows, or keeps records of the status or performance of a particular sector.
-
D.
railwayLineSection
Indicates a specific segment or portion of a railway line that connects two points along the rail network.
-
E.
betweenStreets
Indicates that one location is situated between two specified streets, typically along a road segment bounded by those streets.
- 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef14f9bb4819098e64b527b546d74 |
completed | March 9, 2026, 4:11 p.m. |
Created at: March 9, 2026, 3:20 p.m.