Triple
T37221551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haruka |
E922895
|
entity |
| Predicate | hasLiteralMeaningDescription |
P3918
|
FINISHED |
| Object | Haruka means distant or far away in Japanese |
—
|
NE NERFINISHED |
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: Haruka means distant or far away in Japanese | Statement: [Haruka, hasLiteralMeaningDescription, Haruka means distant or far away in Japanese]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLiteralMeaningDescription Context triple: [Haruka, hasLiteralMeaningDescription, Haruka means distant or far away in Japanese]
-
A.
hasLiteralMeaning
chosen
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
-
B.
hasDescription
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
C.
hasMeaningInOriginLanguage
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning in its original or source language.
-
D.
hasSymbolicInterpretation
Indicates that one entity is understood or used as a symbolic representation or metaphorical stand-in for another entity or concept.
-
E.
hasLinguisticDescriptionBy
Indicates that something is described or characterized using language by a particular source, agent, or medium.
- 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_69f76ea6f5288190b8d9988f613811c0 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff069ec1348190815375c5c9e38404 |
completed | May 9, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69ff05ba57f88190a45d20f18044e0fb |
completed | May 9, 2026, 10 a.m. |
Created at: May 3, 2026, 4:15 p.m.