Triple
T25809366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 丘田 |
E650062
|
entity |
| Predicate | etymologicalElement丘 |
P5801
|
FINISHED |
| Object | topographical feature |
—
|
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: topographical feature | Statement: [丘田, etymologicalElement丘, topographical feature]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: etymologicalElement丘 Context triple: [丘田, etymologicalElement丘, topographical feature]
-
A.
etymologicalField
Indicates that one term belongs to a particular semantic or conceptual domain relevant to its etymological origin or historical development.
-
B.
etymologyPossibleMeaning
Indicates a possible or hypothesized meaning that an etymological analysis suggests for a word or term.
-
C.
etymologicalNote
Indicates that there is a note explaining the origin, historical development, or source language of a term or name.
-
D.
etymologicalSource
chosen
Indicates that one term or name originates from, is derived from, or has its roots in another term or name.
-
E.
etymologicalPattern
Indicates a relationship where one form or set of forms follows a recurring etymological structure or transformation pattern derived from another.
- 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_69e7ab35d264819095367f7e80c983ff |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f600c2a7748190809b59109e476169 |
completed | May 2, 2026, 1:48 p.m. |
| PD | Predicate disambiguation | batch_69f4938b960081909b53c074a3e0c7c2 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 22, 2026, 7:07 a.m.