Triple
T37950389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yibin Wuliangye Airport |
E946725
|
entity |
| Predicate | isNamedAfterIndustry |
P24365
|
FINISHED |
| Object | liquor industry |
—
|
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: liquor industry | Statement: [Yibin Wuliangye Airport, isNamedAfterIndustry, liquor industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isNamedAfterIndustry Context triple: [Yibin Wuliangye Airport, isNamedAfterIndustry, liquor industry]
-
A.
isNamedAfterOccupation
Indicates that an entity’s name is derived from or based on a particular occupation or profession.
-
B.
hasCompanyNamedAfter
Indicates that one entity has a company whose name is derived from or identical to the other entity.
-
C.
oftenNamedAfter
Indicates that one entity frequently receives its name from or in honor of another entity.
-
D.
isNamedFor
chosen
Indicates that one entity bears its name in honor of, or derived from, another entity.
-
E.
hasPlaceNamedAfter
Indicates that one place is named in honor of or derived from the name of another place.
- 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_69f76ef64cf08190ad3e1114b62aac67 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_69fbc7b78f9481909f4f8fc2e3fdcde1 |
completed | May 6, 2026, 10:59 p.m. |
| PD | Predicate disambiguation | batch_69fbbd18c9908190928d274f8731dfa8 |
completed | May 6, 2026, 10:13 p.m. |
Created at: May 3, 2026, 4:20 p.m.