Triple
T26665731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sichuan Airlines |
E672180
|
entity |
| Predicate | operatingAreaSpecialization |
P108435
|
FINISHED |
| Object | Western China |
—
|
NE NERFINISHED |
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: Western China | Statement: [Sichuan Airlines, operatingAreaSpecialization, Western China]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operatingAreaSpecialization Context triple: [Sichuan Airlines, operatingAreaSpecialization, Western China]
-
A.
specializationRegion
Indicates that something is specialized, adapted, or specifically applicable to a particular geographic or spatial region.
-
B.
strategicAreaServed
Indicates that an entity provides services or exerts influence within a particular area considered strategically important.
-
C.
regionSpecialization
Indicates that a region is designated or recognized as being particularly focused on, adapted to, or specialized in a specific function, activity, or domain.
-
D.
operationalSpecialty
chosen
Indicates a relationship where an entity has a particular area of operational focus, expertise, or functional specialization within its activities or duties.
-
E.
areaServedType
Indicates the type or category of area that is served by an entity or service.
- 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_69eecda00a9c8190b2691f4d89db03b6 |
completed | April 27, 2026, 2:44 a.m. |
| NER | Named-entity recognition | batch_69fd64bc86848190a49f451a8fc5cf1e |
completed | May 8, 2026, 4:21 a.m. |
| PD | Predicate disambiguation | batch_69fd5ff4a648819090756d90fd195d9a |
completed | May 8, 2026, 4 a.m. |
Created at: April 27, 2026, 3:09 a.m.