Triple
T20282141
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hayashi |
E503174
|
entity |
| Predicate | sharesKanjiWith |
P44216
|
FINISHED |
| Object | Chinese surname Lin |
—
|
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: Chinese surname Lin | Statement: [Hayashi, sharesKanjiWith, Chinese surname Lin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sharesKanjiWith Context triple: [Hayashi, sharesKanjiWith, Chinese surname Lin]
-
A.
sharesRomanizationWith
Indicates that two distinct written forms are pronounced the same way when transliterated into a shared Romanization system.
-
B.
sharesCharacterWith
chosen
Indicates that two entities have at least one character (such as a letter, symbol, or glyph) in common.
-
C.
sharesLexiconWith
Indicates that two entities use or are associated with the same set of lexical items, vocabulary, or word inventory.
-
D.
sharesMeaningWith
Indicates that two expressions convey the same or very similar meaning, even if they differ in form or wording.
-
E.
sharesUniverseWith
Indicates that two entities exist within the same fictional or narrative universe, implying shared continuity, setting, or canon.
- 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_69e0b4b0e79c8190bd61f22ef1329fa8 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6768f86448190842389a98b93a918 |
completed | April 20, 2026, 6:55 p.m. |
| PD | Predicate disambiguation | batch_69e55b1e5e1c8190ba8a5544b1db9e1d |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 16, 2026, 10:39 a.m.