Triple
T16471946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Na |
E400082
|
entity |
| Predicate | hasHomophonousNames |
P119509
|
FINISHED |
| Object | multiple Chinese characters pronounced Na |
—
|
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: multiple Chinese characters pronounced Na | Statement: [Na, hasHomophonousNames, multiple Chinese characters pronounced Na]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHomophonousNames Context triple: [Na, hasHomophonousNames, multiple Chinese characters pronounced Na]
-
A.
hasHomophones
chosen
Indicates that two or more linguistic expressions share the same pronunciation but differ in meaning, spelling, or both.
-
B.
hasRhymingName
Indicates that one entity has a name that rhymes with the name of another entity.
-
C.
isHomographOf
Indicates that two words share the same written form but have different meanings, and possibly different pronunciations or origins.
-
D.
hasPhonologicalSimilarityTo
Indicates that two linguistic elements share similar sound patterns or phonological features.
-
E.
hasAlternativeNameForSameRace
Indicates that one name is an alternative designation used for the same race as another name.
- 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_69d87f2dac988190b74d6e185fa88ba4 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32dd19df881909e4562a5e8473338 |
completed | April 18, 2026, 7:08 a.m. |
| PD | Predicate disambiguation | batch_69e22706b0588190a48a951c5211a617 |
completed | April 17, 2026, 12:26 p.m. |
Created at: April 10, 2026, 5:11 a.m.