Triple
T24995332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sōeki |
E625551
|
entity |
| Predicate | honorificContext |
P157528
|
FINISHED |
| Object | tea ceremony lineage names |
—
|
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: tea ceremony lineage names | Statement: [Sōeki, honorificContext, tea ceremony lineage names]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorificContext Context triple: [Sōeki, honorificContext, tea ceremony lineage names]
-
A.
honorificSense
Indicates that one entity refers to another using an honorific or respectful linguistic form.
-
B.
honorificUsage
Indicates that one entity refers to or addresses another using an honorific title or respectful linguistic form.
-
C.
honorificUse
Indicates that one entity refers to or addresses another using an honorific title or respectful linguistic form.
-
D.
honorificIndicates
Indicates that one entity uses an honorific title or respectful form of address to refer to or address another entity.
-
E.
honorificType
Indicates the type or category of honorific or formal title associated with an entity in a given context.
- F. None of above. chosen
Provenance (4 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_69e2ff2611c081908710457fbe6d376b |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f44a4a2c048190bfb5afe6df7ca3f0 |
completed | May 1, 2026, 6:38 a.m. |
| PD | Predicate disambiguation | batch_69f442c0c2e88190acd7f170f10ccef6 |
completed | May 1, 2026, 6:05 a.m. |
| PDg | Predicate description generation | batch_69f448fe11f08190bdd53ca7ba2d51e4 |
completed | May 1, 2026, 6:32 a.m. |
Created at: April 18, 2026, 6:04 a.m.