Triple
T23363756
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jang Bogo Station |
E593253
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
JBS
JBS is the commonly used abbreviation for Jang Bogo Station, a South Korean research base in Antarctica.
|
E1583054
|
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: JBS | Statement: [Jang Bogo Station, abbreviation, JBS]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: JBS Context triple: [Jang Bogo Station, abbreviation, JBS]
-
A.
Bunge
Bunge is the unicameral legislative body and main law-making institution of the United Republic of Tanzania.
-
B.
Bunge
Bunge is a surname most notably associated with Nikolai Bunge, a prominent 19th-century Russian economist and statesman.
-
C.
BJ's
BJ's is an American membership-based warehouse club chain offering discounted bulk groceries, household goods, and other merchandise.
-
D.
Bryan Foods
Bryan Foods is an American food company best known for its processed meat products such as sausages, bacon, and lunch meats, particularly popular in the Southern United States.
-
E.
Tyson Foods
Tyson Foods is a major American multinational food company best known as one of the world’s largest processors and marketers of chicken, beef, and pork products.
- 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: JBS Triple: [Jang Bogo Station, abbreviation, JBS]
Generated description
JBS is the commonly used abbreviation for Jang Bogo Station, a South Korean research base in Antarctica.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: JBS Target entity description: JBS is the commonly used abbreviation for Jang Bogo Station, a South Korean research base in Antarctica.
-
A.
Bunge
Bunge is the unicameral legislative body and main law-making institution of the United Republic of Tanzania.
-
B.
Bunge
Bunge is a surname most notably associated with Nikolai Bunge, a prominent 19th-century Russian economist and statesman.
-
C.
BJ's
BJ's is an American membership-based warehouse club chain offering discounted bulk groceries, household goods, and other merchandise.
-
D.
Bryan Foods
Bryan Foods is an American food company best known for its processed meat products such as sausages, bacon, and lunch meats, particularly popular in the Southern United States.
-
E.
Tyson Foods
Tyson Foods is a major American multinational food company best known as one of the world’s largest processors and marketers of chicken, beef, and pork products.
- 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_69e25d2593c88190bcdf4a716a94ccb2 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0aac4248190a4663ed12aed6856 |
completed | April 29, 2026, 6:09 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0c5dd78f508190b3b83e4cc2625163 |
completed | May 19, 2026, 12:55 p.m. |
| NEDg | Description generation | batch_6a0c60473de0819096d3b4e35da16295 |
completed | May 19, 2026, 1:06 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0c60b52fe88190854803902df750c5 |
completed | May 19, 2026, 1:08 p.m. |
Created at: April 17, 2026, 5:31 p.m.