Triple
T24719317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 川越市 |
E612252
|
entity |
| Predicate | 面積_km2 |
P13670
|
FINISHED |
| Object | 約109.13 |
—
|
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: 約109.13 | Statement: [川越市, 面積_km2, 約109.13]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 面積_km2 Context triple: [川越市, 面積_km2, 約109.13]
-
A.
areaTotalSquareKilometers
Indicates the total size of something measured in square kilometers.
-
B.
areaApproxKm2
chosen
Indicates that one entity has an approximate area, measured in square kilometers, given by the other entity.
-
C.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
-
D.
hasAreaRankInTaiwan
Indicates the relative ranking of an entity by its area size compared to other entities within Taiwan.
-
E.
associatedMainlandArea
Indicates a relationship where a non-mainland region (such as an island or territory) is linked to the specific mainland area with which it is geographically, administratively, or politically connected.
- 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_69e2d7d6e7a48190bb43b0d8bb1137a0 |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f410fe3b848190ae296a29f742ee30 |
completed | May 1, 2026, 2:33 a.m. |
| PD | Predicate disambiguation | batch_69f40ee8ada8819089a7016b50308ff0 |
completed | May 1, 2026, 2:24 a.m. |
Created at: April 18, 2026, 3:40 a.m.