Triple

T28373839
Position Surface form Disambiguated ID Type / Status
Subject 竹山县 E718702 entity
Predicate 生态特征 P18514 FINISHED
Object 生态环境良好 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: 生态环境良好 | Statement: [竹山县, 生态特征, 生态环境良好]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: 生态特征
Context triple: [竹山县, 生态特征, 生态环境良好]
  • A. 立地特性
    Indicates the characteristics or qualities of a location that define its situational conditions or advantages in relation to its surroundings.
  • B. ecologicalRelevance
    Indicates that one entity has significance, impact, or importance for the functioning, stability, or dynamics of another entity’s ecosystem or ecological context.
  • C. ecologicalStatus chosen
    Indicates the condition or health of an ecosystem or environment, often in terms of its quality, integrity, or degree of disturbance.
  • D. environmentalSuitability
    Indicates that certain environmental conditions are appropriate or favorable for a particular entity, process, or activity.
  • E. hasEcology
    Indicates that an entity has a particular ecological context, such as its habitat, environmental role, or interactions within an ecosystem.
  • 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_69eff6ee5afc8190bd7375a29f0cc6c6 completed April 27, 2026, 11:53 p.m.
NER Named-entity recognition batch_69f64c5c0ba081908d836393db68b842 completed May 2, 2026, 7:11 p.m.
PD Predicate disambiguation batch_69f641e2f1708190b45b48d6a43c51d2 completed May 2, 2026, 6:26 p.m.
Created at: April 28, 2026, 1:01 a.m.