Triple
T2573376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | California state highway system |
E57713
|
entity |
| Predicate | hasAbbreviation |
P43
|
FINISHED |
| Object |
CA SR
CA SR is the standard abbreviation used to designate numbered state routes within the California state highway system.
|
E278839
|
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: CA SR | Statement: [California state highway system, hasAbbreviation, CA SR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CA SR Context triple: [California state highway system, hasAbbreviation, CA SR]
-
A.
CA
CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
-
B.
CA
CA is the two-letter U.S. postal abbreviation for the state of California.
-
C.
CA
CA is the IATA airline designator assigned to Air China, the flag carrier of the People's Republic of China.
-
D.
San Mateo County, California
San Mateo County, California is a coastal county in the San Francisco Bay Area known for its affluent communities, tech industry presence, and proximity to both San Francisco and Silicon Valley.
-
E.
Santa Clara, California, United States
Santa Clara is a major city in California’s Silicon Valley known for its concentration of high-tech companies, including serving as a key hub for the technology industry in the United States.
- 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: CA SR Triple: [California state highway system, hasAbbreviation, CA SR]
Generated description
CA SR is the standard abbreviation used to designate numbered state routes within the California state highway system.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CA SR Target entity description: CA SR is the standard abbreviation used to designate numbered state routes within the California state highway system.
-
A.
CA
CA is the two-letter ISO 3166-1 alpha-2 country code that uniquely identifies Canada in international standards and systems.
-
B.
CA
CA is the IATA airline designator assigned to Air China, the flag carrier of the People's Republic of China.
-
C.
CA
CA is the two-letter U.S. postal abbreviation for the state of California.
-
D.
San Mateo County, California
San Mateo County, California is a coastal county in the San Francisco Bay Area known for its affluent communities, tech industry presence, and proximity to both San Francisco and Silicon Valley.
-
E.
Santa Clara, California, United States
Santa Clara is a major city in California’s Silicon Valley known for its concentration of high-tech companies, including serving as a key hub for the technology industry in the United States.
- 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_69ab4a51410081908501dcf8bad9adc4 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd38792288190a39420cab126bf03 |
completed | March 7, 2026, 7:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af657413908190a03b9dd8dc40b2e4 |
completed | March 10, 2026, 12:27 a.m. |
| NEDg | Description generation | batch_69af67cbaf388190b5bb447af2a8e941 |
completed | March 10, 2026, 12:37 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69af682b38d08190bba53245e813f044 |
completed | March 10, 2026, 12:39 a.m. |
Created at: March 6, 2026, 9:48 p.m.