Triple
T14423155
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Naver Corporation |
E357631
|
entity |
| Predicate | operates |
P24
|
FINISHED |
| Object |
Naver Cafe
Naver Cafe is a South Korean online community platform that hosts user-created forums and interest-based groups within the Naver ecosystem.
|
E1099179
|
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: Naver Cafe | Statement: [Naver Corporation, operates, Naver Cafe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Naver Cafe Context triple: [Naver Corporation, operates, Naver Cafe]
-
A.
Wolmi Culture Street
Wolmi Culture Street is a popular cultural and leisure district on Wolmido Island in Incheon, South Korea, known for its seaside promenade, cafes, street performances, and vibrant night views.
-
B.
Hongdae
Hongdae is a vibrant neighborhood in Seoul known for its indie music scene, street art, nightlife, and youth culture centered around Hongik University.
-
C.
Nam-gu Office
Nam-gu Office is the district-level local government administration for Nam District in Busan, South Korea.
-
D.
Baeggu
Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
-
E.
Naewon-sa
Naewon-sa is a historic Buddhist temple in Yangsan, South Korea, known for its tranquil mountain setting and traditional Korean temple architecture.
- 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: Naver Cafe Triple: [Naver Corporation, operates, Naver Cafe]
Generated description
Naver Cafe is a South Korean online community platform that hosts user-created forums and interest-based groups within the Naver ecosystem.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Naver Cafe Target entity description: Naver Cafe is a South Korean online community platform that hosts user-created forums and interest-based groups within the Naver ecosystem.
-
A.
Wolmi Culture Street
Wolmi Culture Street is a popular cultural and leisure district on Wolmido Island in Incheon, South Korea, known for its seaside promenade, cafes, street performances, and vibrant night views.
-
B.
Hongdae
Hongdae is a vibrant neighborhood in Seoul known for its indie music scene, street art, nightlife, and youth culture centered around Hongik University.
-
C.
Nam-gu Office
Nam-gu Office is the district-level local government administration for Nam District in Busan, South Korea.
-
D.
Baeggu
Baeggu is an Oceanic language of the Meso-Melanesian group spoken by a small community in the Solomon Islands.
-
E.
Naewon-sa
Naewon-sa is a historic Buddhist temple in Yangsan, South Korea, known for its tranquil mountain setting and traditional Korean temple architecture.
- 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_69d82793421c8190861eb0e673b085de |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de91102c3c81908f571a1fff3bdd47 |
completed | April 14, 2026, 7:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd5bcd2a908190ad7d5ebf11b41551 |
completed | May 8, 2026, 3:43 a.m. |
| NEDg | Description generation | batch_69fd5d585cc08190908bc5f9b8abdb82 |
completed | May 8, 2026, 3:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd5e0bbd6c8190b14039b3335692c7 |
completed | May 8, 2026, 3:52 a.m. |
Created at: April 10, 2026, 1:18 a.m.