Triple
T18516381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 21 (Shenzhen Metro) |
E452473
|
entity |
| Predicate | hasPlannedOperatorType |
P131970
|
FINISHED |
| Object | state-owned enterprise |
—
|
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: state-owned enterprise | Statement: [Line 21 (Shenzhen Metro), hasPlannedOperatorType, state-owned enterprise]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlannedOperatorType Context triple: [Line 21 (Shenzhen Metro), hasPlannedOperatorType, state-owned enterprise]
-
A.
hasPlanningType
Indicates that an entity is associated with a specific category or type used for planning or scheduling purposes.
-
B.
hasOperationType
Indicates the specific kind or category of operation associated with an entity or process.
-
C.
hasPlanner
Indicates that an entity is associated with or assigned a planner responsible for organizing or managing its activities or processes.
-
D.
operatorPlanned
Indicates that an operator has scheduled or arranged a specific action, process, or operation to occur.
-
E.
hasMajorOperator
Indicates that an entity is primarily operated, managed, or run by a specified main operator or organization.
- F. None of above. chosen
Provenance (4 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_69d8d386df84819092355ebb260d848e |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5338a628c81909db08ae7dc94f59a |
completed | April 19, 2026, 7:56 p.m. |
| PD | Predicate disambiguation | batch_69e469e0025c81908f16ed4f922674af |
completed | April 19, 2026, 5:36 a.m. |
| PDg | Predicate description generation | batch_69e46d2b93bc8190a6070018d7046547 |
completed | April 19, 2026, 5:50 a.m. |
Created at: April 10, 2026, 11:36 a.m.