Triple
T22837400
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heo |
E565983
|
entity |
| Predicate | isFamilyNameOf |
P18
|
FINISHED |
| Object |
Heo Hoon
Heo Hoon is a South Korean professional basketball player known for his playmaking and scoring ability in the Korean Basketball League.
|
E1561514
|
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: Heo Hoon | Statement: [Heo, isFamilyNameOf, Heo Hoon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heo Hoon Context triple: [Heo, isFamilyNameOf, Heo Hoon]
-
A.
Heo Eung-soo
Heo Eung-soo was a South Korean entrepreneur best known as the founder of the LG Group, one of the country’s largest and most influential conglomerates.
-
B.
Dong Hee-seon
Dong Hee-seon is a South Korean screenwriter best known for her work on the hit fantasy-comedy film "Miss Granny."
-
C.
Heo Jun
Heo Jun was a prominent 16th-century Korean royal physician and scholar best known for compiling the influential medical text "Dongui Bogam."
-
D.
Byeon Bong-seon
Byeon Bong-seon is a South Korean cinematographer known for his work on the sci-fi film "Space Sweepers."
-
E.
Suh Kyung-bae
Suh Kyung-bae is a South Korean billionaire businessman best known as the chairman of Amorepacific Corporation, one of Asia’s leading cosmetics companies.
- 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: Heo Hoon Triple: [Heo, isFamilyNameOf, Heo Hoon]
Generated description
Heo Hoon is a South Korean professional basketball player known for his playmaking and scoring ability in the Korean Basketball League.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Heo Hoon Target entity description: Heo Hoon is a South Korean professional basketball player known for his playmaking and scoring ability in the Korean Basketball League.
-
A.
Heo Eung-soo
Heo Eung-soo was a South Korean entrepreneur best known as the founder of the LG Group, one of the country’s largest and most influential conglomerates.
-
B.
Dong Hee-seon
Dong Hee-seon is a South Korean screenwriter best known for her work on the hit fantasy-comedy film "Miss Granny."
-
C.
Heo Jun
Heo Jun was a prominent 16th-century Korean royal physician and scholar best known for compiling the influential medical text "Dongui Bogam."
-
D.
Byeon Bong-seon
Byeon Bong-seon is a South Korean cinematographer known for his work on the sci-fi film "Space Sweepers."
-
E.
Suh Kyung-bae
Suh Kyung-bae is a South Korean billionaire businessman best known as the chairman of Amorepacific Corporation, one of Asia’s leading cosmetics companies.
- 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_69e245869e188190a196584f36e682da |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17e303cec81909c5c118dc8c93354 |
completed | April 29, 2026, 3:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0bc2337900819098b989c47219bc1d |
completed | May 19, 2026, 1:51 a.m. |
| NEDg | Description generation | batch_6a0bc2fa53788190bfedeb5bcbfd0876 |
completed | May 19, 2026, 1:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0bc3c11ebc8190995c0025a594d40a |
completed | May 19, 2026, 1:58 a.m. |
Created at: April 17, 2026, 3:35 p.m.