Triple
T7155153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Library of Korea |
E166788
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object |
NLK
NLK is the National Library of Korea, the country’s central repository for published materials and a key institution for preserving and providing access to Korea’s documentary heritage.
|
E644916
|
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: NLK | Statement: [National Library of Korea, abbreviation, NLK]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NLK Context triple: [National Library of Korea, abbreviation, NLK]
-
A.
NIKL
NIKL is the abbreviated name of South Korea’s National Institute of Korean Language, the government body responsible for researching, standardizing, and promoting the Korean language.
-
B.
Nelis
Nelis is a Dutch given name commonly used as a diminutive or familiar form of Cornelis.
-
C.
Nelonen
Nelonen is a prominent Finnish commercial television channel known for broadcasting a wide range of entertainment, drama, reality shows, and sports programming.
-
D.
Nel
Nel is a diminutive form of the given name Cornelia, commonly used as a short or affectionate version of the name.
-
E.
Nalik
Nalik is an Austronesian language spoken by a small community in New Ireland, Papua New Guinea.
- 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: NLK Triple: [National Library of Korea, abbreviation, NLK]
Generated description
NLK is the National Library of Korea, the country’s central repository for published materials and a key institution for preserving and providing access to Korea’s documentary heritage.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: NLK Target entity description: NLK is the National Library of Korea, the country’s central repository for published materials and a key institution for preserving and providing access to Korea’s documentary heritage.
-
A.
NIKL
NIKL is the abbreviated name of South Korea’s National Institute of Korean Language, the government body responsible for researching, standardizing, and promoting the Korean language.
-
B.
Nelis
Nelis is a Dutch given name commonly used as a diminutive or familiar form of Cornelis.
-
C.
Nelonen
Nelonen is a prominent Finnish commercial television channel known for broadcasting a wide range of entertainment, drama, reality shows, and sports programming.
-
D.
Nel
Nel is a diminutive form of the given name Cornelia, commonly used as a short or affectionate version of the name.
-
E.
Nalik
Nalik is an Austronesian language spoken by a small community in New Ireland, Papua New Guinea.
- 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_69c68887a5cc8190bec0ea96227164f7 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e80c747c8190a017a2b1c3e78a3f |
completed | March 27, 2026, 8:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7adb0ea288190b7eef76de30a3a1e |
completed | March 28, 2026, 10:30 a.m. |
| NEDg | Description generation | batch_69c7ae1bde448190b546d292d213c8c9 |
completed | March 28, 2026, 10:31 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7ae73e1a88190a18488b3155b2542 |
completed | March 28, 2026, 10:33 a.m. |
Created at: March 27, 2026, 2:47 p.m.