Triple
T1532090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Columbus Crew |
E32464
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object |
CLB
CLB is the abbreviated short name commonly used for the Major League Soccer club Columbus Crew.
|
E173665
|
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: CLB | Statement: [Columbus Crew, shortName, CLB]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CLB Context triple: [Columbus Crew, shortName, CLB]
-
A.
CLB
CLB is the abbreviated name for Japan’s Cabinet Legislation Bureau, the government body that reviews and drafts legislation and advises the Cabinet on legal matters.
-
B.
CL 9
CL 9 is a technology company co-founded by Apple co-founder Steve Wozniak, focused on cloud computing and data center services.
-
C.
CLU
CLU is an early high-level programming language from the 1970s that pioneered data abstraction, iterators, and exception handling, significantly influencing the design of later languages.
-
D.
Club 152
Club 152 is a popular multi-level bar and live music venue on Memphis’s historic Beale Street, known for its energetic nightlife and performances.
-
E.
Club C
Club C is a classic Reebok sneaker line known for its clean, minimalist tennis-inspired design and everyday casual wear appeal.
- 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: CLB Triple: [Columbus Crew, shortName, CLB]
Generated description
CLB is the abbreviated short name commonly used for the Major League Soccer club Columbus Crew.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CLB Target entity description: CLB is the abbreviated short name commonly used for the Major League Soccer club Columbus Crew.
-
A.
CLB
CLB is the abbreviated name for Japan’s Cabinet Legislation Bureau, the government body that reviews and drafts legislation and advises the Cabinet on legal matters.
-
B.
CL 9
CL 9 is a technology company co-founded by Apple co-founder Steve Wozniak, focused on cloud computing and data center services.
-
C.
CLU
CLU is an early high-level programming language from the 1970s that pioneered data abstraction, iterators, and exception handling, significantly influencing the design of later languages.
-
D.
Club 152
Club 152 is a popular multi-level bar and live music venue on Memphis’s historic Beale Street, known for its energetic nightlife and performances.
-
E.
Club C
Club C is a classic Reebok sneaker line known for its clean, minimalist tennis-inspired design and everyday casual wear appeal.
- 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_69a885ea86308190998f6bc14bb91f8e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a90816b5e88190aa92a8558e35744b |
completed | March 5, 2026, 4:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad295a03d881909071fb437c2d19ba |
completed | March 8, 2026, 7:46 a.m. |
| NEDg | Description generation | batch_69ad2a18a79c81908f04ba9aa55d52a0 |
completed | March 8, 2026, 7:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ad2a8deae8819095731fdd1b4bd310 |
completed | March 8, 2026, 7:51 a.m. |
Created at: March 4, 2026, 7:26 p.m.