Triple
T1724081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mie Prefecture |
E37456
|
entity |
| Predicate | hasSeafoodIndustry |
P20603
|
FINISHED |
| Object | pearl farming |
—
|
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: pearl farming | Statement: [Mie Prefecture, hasSeafoodIndustry, pearl farming]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeafoodIndustry Context triple: [Mie Prefecture, hasSeafoodIndustry, pearl farming]
-
A.
hasMarineResource
Indicates that one entity possesses, contains, or is associated with a marine (ocean or sea-based) resource in relation to another entity.
-
B.
hasIndustrialSector
chosen
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
C.
hasMarineSpecies
Indicates that an entity contains, supports, or is associated with one or more marine species.
-
D.
hasSmallTownIndustry
Indicates that a small town possesses or supports a particular type of industry or industrial activity.
-
E.
hasUnderwaterThemedRestaurant
Indicates that an entity operates or contains a restaurant whose design, ambiance, or concept is themed around underwater or oceanic elements.
- 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_69a8861acab88190bb43cde203429399 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aadb7bda1081908f2c41c520c9c55c |
completed | March 6, 2026, 1:49 p.m. |
| PD | Predicate disambiguation | batch_69aa61c0a0288190bce9d60062a84b69 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:30 p.m.