Triple
T2656146
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boys, be ambitious |
E54613
|
entity |
| Predicate | hasJapaneseRendering |
P31360
|
FINISHED |
| Object | 少年よ、大志を抱け |
—
|
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: 少年よ、大志を抱け | Statement: [Boys, be ambitious, hasJapaneseRendering, 少年よ、大志を抱け]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJapaneseRendering Context triple: [Boys, be ambitious, hasJapaneseRendering, 少年よ、大志を抱け]
-
A.
hasJapaneseText
chosen
Indicates that an entity contains or is associated with text written in the Japanese language.
-
B.
hasNameInJapanese
Indicates that an entity is associated with a specific name expressed in the Japanese language.
-
C.
usesKatakanaFor
Indicates that one entity is written or represented using katakana script in relation to another entity.
-
D.
hasRomanizationOf
Indicates that one entity is a romanized representation (written in the Latin alphabet) of the other entity’s original script form.
-
E.
hasUnicode
Indicates that an entity is associated with, represented by, or encoded using a specific Unicode character or sequence.
- 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_69ab49e028948190b97e01d73548b1d9 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abda0ba2208190ad87763ecbef8c3c |
completed | March 7, 2026, 7:55 a.m. |
| PD | Predicate disambiguation | batch_69abd815d06481909535c02b0aba8553 |
completed | March 7, 2026, 7:47 a.m. |
Created at: March 6, 2026, 9:53 p.m.