Triple
T8799584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairfield and Suisun Transit |
E209367
|
entity |
| Predicate | hasOfficialAbbreviation |
P8075
|
FINISHED |
| Object |
FAST
FAST is the public bus transit system serving the Fairfield and Suisun City area in Solano County, California.
|
E759856
|
NE FINISHED |
How this triple was built (4 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: FAST | Statement: [Fairfield and Suisun Transit, hasOfficialAbbreviation, FAST]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FAST Context triple: [Fairfield and Suisun Transit, hasOfficialAbbreviation, FAST]
-
A.
FAST
FAST is a U.S. federal law that authorizes long-term funding and policy for the nation’s surface transportation infrastructure, including highways, transit, and rail.
-
B.
Fast
Fast is a surname most notably associated with American novelist and screenwriter Howard Fast, known for his historical and political works.
-
C.
Fastiv
Fastiv is a historic city in northern Ukraine known as a regional railway hub and industrial center southwest of Kyiv.
-
D.
Quick
Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
-
E.
Faster
Faster is a 2010 American action thriller film starring Dwayne Johnson as an ex-con seeking revenge after his brother’s murder.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: FAST Triple: [Fairfield and Suisun Transit, hasOfficialAbbreviation, FAST]
Generated description
FAST is the public bus transit system serving the Fairfield and Suisun City area in Solano County, California.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FAST Target entity description: FAST is the public bus transit system serving the Fairfield and Suisun City area in Solano County, California.
-
A.
FAST
FAST is a U.S. federal law that authorizes long-term funding and policy for the nation’s surface transportation infrastructure, including highways, transit, and rail.
-
B.
Fast
Fast is a surname most notably associated with American novelist and screenwriter Howard Fast, known for his historical and political works.
-
C.
Fastiv
Fastiv is a historic city in northern Ukraine known as a regional railway hub and industrial center southwest of Kyiv.
-
D.
Quick
Quick is the fast-talking, street-smart protagonist played by Eddie Murphy in the 1989 crime-comedy film "Harlem Nights."
-
E.
Faster
Faster is a 2010 American action thriller film starring Dwayne Johnson as an ex-con seeking revenge after his brother’s murder.
- F. None of above. chosen
Provenance (5 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_69ca836240888190a62b262e56a69d2f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5fb7491c8190bcdb98d6cc003d9e |
completed | March 31, 2026, 11:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cf6f658f248190957eba821b07cc4f |
completed | April 3, 2026, 7:42 a.m. |
| NEDg | Description generation | batch_69cf713a184c8190b1fa788fd3ba8304 |
completed | April 3, 2026, 7:50 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cf71d3517c819088c930ed468c4e8e |
completed | April 3, 2026, 7:52 a.m. |
Created at: March 30, 2026, 6:44 p.m.