Triple
T31253832
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tie Luo Han |
E796903
|
entity |
| Predicate | teaSubcategory |
P53105
|
FINISHED |
| Object | yancha |
—
|
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: yancha | Statement: [Tie Luo Han, teaSubcategory, yancha]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teaSubcategory Context triple: [Tie Luo Han, teaSubcategory, yancha]
-
A.
teaCategory
Indicates that one item is classified as belonging to a particular category or type of tea.
-
B.
teaType
chosen
Indicates the specific variety or category of tea associated with an entity.
-
C.
teaProduct
Indicates that something is a product related to tea, such as an item made from, flavored with, or intended for preparing or consuming tea.
-
D.
teaBrand
Indicates that one entity is a brand or producer associated with a particular type or product line of tea for the other entity.
-
E.
teaCulture
Indicates the relationship in which practices, rituals, and social norms surrounding the preparation and consumption of tea are shared, expressed, or maintained.
- 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_69f224dc84d0819081f1cb6f9127e6b1 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d1bf8cc8190a78dfa5ab00daf3a |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:12 p.m.