Triple
T25962654
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rungna Island |
E645581
|
entity |
| Predicate | hasNameInMcCuneReischauer |
P78997
|
FINISHED |
| Object |
Rŭngna-sŏm
Rŭngna-sŏm is a river island in Pyongyang, North Korea, known for its large amusement park and recreational facilities.
|
E1706202
|
NE FINISHED |
How this triple was built (3 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: Rŭngna-sŏm | Statement: [Rungna Island, hasNameInMcCuneReischauer, Rŭngna-sŏm]
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: Rŭngna-sŏm Triple: [Rungna Island, hasNameInMcCuneReischauer, Rŭngna-sŏm]
Generated description
Rŭngna-sŏm is a river island in Pyongyang, North Korea, known for its large amusement park and recreational facilities.
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNameInMcCuneReischauer Context triple: [Rungna Island, hasNameInMcCuneReischauer, Rŭngna-sŏm]
-
A.
nameInMcCuneReischauer
chosen
Indicates that an entity’s name is represented using the McCune–Reischauer romanization system.
-
B.
hasNameInKanji
Indicates that an entity is associated with a specific written form of its name in Kanji characters.
-
C.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
D.
hasOkinawanName
Indicates that an entity possesses a specific name in the Okinawan language.
-
E.
nameInJapaneseKana
Indicates that an entity’s name is written or represented using Japanese kana characters.
- F. None of above.
Provenance (6 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_69e77e85efc08190997da7fcf98bd300 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1107812d98819087412fa54871d074 |
completed | May 23, 2026, 1:48 a.m. |
| NEDg | Description generation | batch_6a111271795081908b2a0d64a713e0a4 |
completed | May 23, 2026, 2:35 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a11151f47e081908fa594fd1f5b5d93 |
completed | May 23, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 22, 2026, 8:47 a.m.