Triple
T24800470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rooster Dragon Mountain |
E620508
|
entity |
| Predicate | literalEnglishMeaningOf |
P103900
|
FINISHED |
| Object | Gyeryongsan |
—
|
LITERAL FINISHED |
How this triple was built (2 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: Gyeryongsan | Statement: [Rooster Dragon Mountain, literalEnglishMeaningOf, Gyeryongsan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literalEnglishMeaningOf Context triple: [Rooster Dragon Mountain, literalEnglishMeaningOf, Gyeryongsan]
-
A.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
B.
textMeaning
chosen
Indicates that one text expresses, conveys, or corresponds to a particular meaning or semantic content.
-
C.
literalMeaningApproximation
Indicates that one entity expresses an approximate or rough literal meaning of another entity, rather than an exact or fully precise interpretation.
-
D.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
-
E.
letterMeaning
Indicates that a particular letter conveys a specific meaning, interpretation, or semantic content.
- F. None of above.
Provenance (3 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_69e2fabe77c8819085f7ce6486248139 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f47b865df48190bf4b6d3e9f9305e6 |
completed | May 1, 2026, 10:08 a.m. |
| PD | Predicate disambiguation | batch_69f4682c8a3c8190adbfaac99474eaaf |
completed | May 1, 2026, 8:45 a.m. |
Created at: April 18, 2026, 4:49 a.m.