Triple
T38569430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liquor City |
E929221
|
entity |
| Predicate | hasChineseEquivalentName |
P54502
|
FINISHED |
| Object | 酒城 |
—
|
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: 酒城 | Statement: [Liquor City, hasChineseEquivalentName, 酒城]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChineseEquivalentName Context triple: [Liquor City, hasChineseEquivalentName, 酒城]
-
A.
hasChineseNameComponent
Indicates that an entity’s Chinese name includes a specific component, such as a particular character, syllable, or segment.
-
B.
hasChineseNameType
Indicates that an entity’s Chinese name belongs to a particular type or category (e.g., formal, short, transliterated).
-
C.
hasEthnonymInChinese
Indicates that an entity has a specific ethnonym (name for an ethnic group or people) expressed in the Chinese language.
-
D.
hasChineseVersion
chosen
Indicates that an entity has a corresponding version or representation available in Chinese.
-
E.
hasEnglishName
Indicates that an entity is associated with a name expressed in the English language.
- 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_69f76ebd2248819083978362d81fa35e |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff5b233e9c8190adc06cca0758986b |
completed | May 9, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69ff5a5682108190a006b23c4fcdcc7c |
completed | May 9, 2026, 4:01 p.m. |
Created at: May 3, 2026, 4:32 p.m.