Triple
T6225833
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kelan Martin |
E139229
|
entity |
| Predicate | twitterUsername |
P2943
|
FINISHED |
| Object |
kelan30_
kelan30_ is the Twitter username of American professional basketball player Kelan Martin, known for his collegiate career at Butler and time in the NBA.
|
E576898
|
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: kelan30_ | Statement: [Kelan Martin, twitterUsername, kelan30_]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: kelan30_ Context triple: [Kelan Martin, twitterUsername, kelan30_]
-
A.
KLE
KLE is the vehicle registration code for the district of Cleves (Kleve) in the German state of North Rhine-Westphalia.
-
B.
KALO
KALO is the ICAO airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
-
C.
KLAL
KLAL is the ICAO airport code for Lakeland Linder International Airport in Lakeland, Florida, a regional airport known for general aviation and cargo operations.
-
D.
KOKSH
KOKSH is the Albanian National Olympic Committee responsible for organizing the country's participation in the Olympic Games and promoting the Olympic movement in Albania.
-
E.
KONT
KONT is the ICAO airport code for Ontario International Airport, a major commercial airport serving the Inland Empire region of Southern California.
- 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: kelan30_ Triple: [Kelan Martin, twitterUsername, kelan30_]
Generated description
kelan30_ is the Twitter username of American professional basketball player Kelan Martin, known for his collegiate career at Butler and time in the NBA.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: kelan30_ Target entity description: kelan30_ is the Twitter username of American professional basketball player Kelan Martin, known for his collegiate career at Butler and time in the NBA.
-
A.
KLE
KLE is the vehicle registration code for the district of Cleves (Kleve) in the German state of North Rhine-Westphalia.
-
B.
KALO
KALO is the ICAO airport code for Waterloo Regional Airport in Waterloo, Iowa, United States.
-
C.
KLAL
KLAL is the ICAO airport code for Lakeland Linder International Airport in Lakeland, Florida, a regional airport known for general aviation and cargo operations.
-
D.
KOKSH
KOKSH is the Albanian National Olympic Committee responsible for organizing the country's participation in the Olympic Games and promoting the Olympic movement in Albania.
-
E.
KONT
KONT is the ICAO airport code for Ontario International Airport, a major commercial airport serving the Inland Empire region of Southern California.
- 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_69c008afd3148190b71e9eaa60420dd1 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c062d42c688190be4d8d8325d6daaa |
completed | March 22, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20dd3dc5c8190bf48da3a90863727 |
completed | March 24, 2026, 4:06 a.m. |
| NEDg | Description generation | batch_69c21131f31881909704aac2130d25a7 |
completed | March 24, 2026, 4:21 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c2118792948190b54b6b54d52d291d |
completed | March 24, 2026, 4:22 a.m. |
Created at: March 22, 2026, 4:22 p.m.