Triple
T33362154
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Qian |
E854249
|
entity |
| Predicate | isHomophonousWithOtherNames |
P119509
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Qian, isHomophonousWithOtherNames, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isHomophonousWithOtherNames Context triple: [Qian, isHomophonousWithOtherNames, yes]
-
A.
hasHomophones
chosen
Indicates that two or more linguistic expressions share the same pronunciation but differ in meaning, spelling, or both.
-
B.
isHomographOf
Indicates that two words share the same written form but have different meanings, and possibly different pronunciations or origins.
-
C.
hasRhymingName
Indicates that one entity has a name that rhymes with the name of another entity.
-
D.
hasGivenNameCounterpart
Indicates that one entity is the given-name (first-name) counterpart or variant of another entity, typically linking related personal names.
-
E.
heteronymOf
Indicates that two words share the same spelling but differ in pronunciation and meaning.
- 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_69f3496bda8c8190bfc8fade9d1b791c |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6e3156ea48190b604e414665ef351 |
completed | May 3, 2026, 5:54 a.m. |
| PD | Predicate disambiguation | batch_69f6de0b9ba48190887c9eb5d06a2e94 |
completed | May 3, 2026, 5:32 a.m. |
Created at: May 1, 2026, 1:34 a.m.