Triple
T3847942
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beijing Daxing International Airport |
E85217
|
entity |
| Predicate | hasTerminalShape |
P51911
|
FINISHED |
| Object | starfish-shaped |
—
|
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: starfish-shaped | Statement: [Beijing Daxing International Airport, hasTerminalShape, starfish-shaped]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTerminalShape Context triple: [Beijing Daxing International Airport, hasTerminalShape, starfish-shaped]
-
A.
hasTerminalFunction
Indicates that something possesses a function or role specifically associated with an endpoint, boundary, or final stage within a system or process.
-
B.
hasSubTerminal
Indicates that an entity includes or is associated with a subordinate or lower-level terminal element within a hierarchical structure.
-
C.
hasTerminusIn
Indicates that something (such as a route, line, or path) ends or has its final stopping point at a specified location.
-
D.
hasSilhouetteShape
Indicates that one entity has the overall outline or contour shape specified or characterized by another entity.
-
E.
hasIntegratedTerminal
Indicates that one entity includes or supports a built-in terminal interface as part of its functionality.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeebcc8a0481909c35161336bdfbf9 |
completed | March 9, 2026, 3:48 p.m. |
| PD | Predicate disambiguation | batch_69aee750377c8190af70c79768c0edd8 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aee8d9b328819080158be59e5bcc97 |
completed | March 9, 2026, 3:35 p.m. |
Created at: March 9, 2026, 3:18 p.m.