Triple
T1644246
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DART bus network |
E35542
|
entity |
| Predicate | connectsWith |
P37
|
FINISHED |
| Object | DART Light Rail |
E51093
|
NE 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: DART Light Rail | Statement: [DART bus network, connectsWith, DART Light Rail]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: DART Light Rail Context triple: [DART bus network, connectsWith, DART Light Rail]
-
A.
DART Light Rail
chosen
DART Light Rail is a light rail transit system serving the Dallas–Fort Worth metropolitan area, operated by Dallas Area Rapid Transit.
-
B.
MAX Light Rail
MAX Light Rail is the metropolitan light rail transit system serving the Portland, Oregon, metropolitan area.
-
C.
DART Blue Line
The DART Blue Line is a light rail service in the Dallas Area Rapid Transit system that runs through key parts of Dallas and its surrounding communities.
-
D.
DART Red Line
The DART Red Line is a light rail service in Dallas, Texas, forming one of the primary routes in the Dallas Area Rapid Transit rail network.
-
E.
METRO light rail
METRO light rail is a rapid transit system serving the Minneapolis–Saint Paul metropolitan area with multiple color-designated lines connecting key urban, suburban, and airport destinations.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa622e9b08819094960b2329c6e7e6 |
completed | March 6, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad8aba8d4c819098be250f8487df45 |
completed | March 8, 2026, 2:42 p.m. |
Created at: March 4, 2026, 7:28 p.m.