Triple
T6543058
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Y Yen District |
E168336
|
entity |
| Predicate | hasCraftIndustry |
P19189
|
FINISHED |
| Object | traditional handicrafts |
—
|
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: traditional handicrafts | Statement: [Y Yen District, hasCraftIndustry, traditional handicrafts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCraftIndustry Context triple: [Y Yen District, hasCraftIndustry, traditional handicrafts]
-
A.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
B.
hasCraft
Indicates a relationship where an entity possesses, operates, or is associated with a particular vehicle, vessel, or other craft.
-
C.
hasSmallTownIndustry
chosen
Indicates that a small town possesses or supports a particular type of industry or industrial activity.
-
D.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
-
E.
hasCraftsman
Indicates that one entity serves as the craftsman, maker, or artisan responsible for creating, building, or crafting another entity.
- 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_69c68a51564081909e93aee0dbd9cca3 |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6ce07332481909a5a7964282eb776 |
completed | March 27, 2026, 6:35 p.m. |
| PD | Predicate disambiguation | batch_69c6acf3e3708190b052ec774e607cb7 |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:50 p.m.