Triple
T15554211
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Muni Metro lines |
E370826
|
entity |
| Predicate | fareIntegrationWith |
P3494
|
FINISHED |
| Object | Muni buses |
E39999
|
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: Muni buses | Statement: [Muni Metro lines, fareIntegrationWith, Muni buses]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Muni buses Context triple: [Muni Metro lines, fareIntegrationWith, Muni buses]
-
A.
Muni bus network
chosen
The Muni bus network is San Francisco’s citywide public transit system of buses and trolleybuses that provides comprehensive surface transportation across the city.
-
B.
MUNI
MUNI is the commonly used abbreviation for Masaryk University, a major public research university based in Brno, Czech Republic.
-
C.
Muni Metro lines
Muni Metro lines are a network of light rail routes in San Francisco that provide rapid transit service across the city as part of the San Francisco Municipal Railway system.
-
D.
Muni Metro
Muni Metro is San Francisco’s light rail and streetcar system, forming a core part of the city’s public transit network.
-
E.
Metro Bus
Metro Bus is the primary public bus service network for Los Angeles County, providing extensive local and rapid transit across the region.
- 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_69d85cc6cf40819091f4a5facee1ebe6 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04a96c0c88190808f68601a36b506 |
completed | April 16, 2026, 2:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff456209288190aba6debd434af741 |
completed | May 9, 2026, 2:32 p.m. |
Created at: April 10, 2026, 4:09 a.m.