Triple
T32507499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chenggu County |
E830838
|
entity |
| Predicate | hasTertiaryIndustry |
P69121
|
FINISHED |
| Object | local services |
—
|
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: local services | Statement: [Chenggu County, hasTertiaryIndustry, local services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTertiaryIndustry Context triple: [Chenggu County, hasTertiaryIndustry, local services]
-
A.
hasTertiaryEconomicSector
chosen
Indicates that an entity participates in or possesses activities belonging to the tertiary (service) sector of the economy, such as services rather than primary or secondary production.
-
B.
hasSecondaryIndustry
Indicates that an entity is associated with an additional, non-primary industry in which it operates or participates.
-
C.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
D.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
E.
hasTertiaryLandUse
Indicates that an entity is associated with a third-level or additional land use classification beyond its primary and secondary land uses.
- 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_69f3492318348190ba37fb6b5f1d67f4 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
Created at: May 1, 2026, 1 a.m.