Triple
T18550690
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 22 (Shenzhen Metro) |
E453365
|
entity |
| Predicate | isInPlanningStage |
P24929
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Line 22 (Shenzhen Metro), isInPlanningStage, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isInPlanningStage Context triple: [Line 22 (Shenzhen Metro), isInPlanningStage, yes]
-
A.
hasPlanningStatus
chosen
Indicates that an entity is associated with a particular stage, condition, or outcome in a planning or approval process.
-
B.
hasPlanningLevel
Indicates that an entity is associated with a specific stage, tier, or granularity within a planning or scheduling hierarchy.
-
C.
hasPlanningType
Indicates that an entity is associated with a specific category or type used for planning or scheduling purposes.
-
D.
plannedIn
Indicates that an event, activity, or process is scheduled or arranged to occur within a specific context, timeframe, or plan.
-
E.
hasPlanningContext
Indicates that an entity is associated with a specific planning-related situation, scope, or set of conditions that frame how it should be interpreted or used.
- 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53800c0fc819097782f1e81574598 |
completed | April 19, 2026, 8:16 p.m. |
| PD | Predicate disambiguation | batch_69e469e274a48190a570b25cfef4d890 |
completed | April 19, 2026, 5:36 a.m. |
Created at: April 10, 2026, 11:38 a.m.