Triple
T10082268
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro Line 4 |
E213929
|
entity |
| Predicate | hasLoopSection |
P36766
|
FINISHED |
| Object | full circle |
—
|
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: full circle | Statement: [Shanghai Metro Line 4, hasLoopSection, full circle]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLoopSection Context triple: [Shanghai Metro Line 4, hasLoopSection, full circle]
-
A.
hasPassingLoopAt
Indicates that a railway line or track segment includes a passing loop located at a specified place or point.
-
B.
isLoop
chosen
Indicates that something forms or behaves as a closed, repeating cycle or path that returns to its starting point.
-
C.
hasSectionOpening
Indicates that one entity serves as the opening or introductory section of another, typically larger, entity.
-
D.
loopLocation
Indicates the specific place or context in which a loop occurs or is situated.
-
E.
loopsFrom
Indicates that a path, process, or connection starts at a given point and returns back to that same point, forming a loop.
- 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_69ca839bf730819086900c323c9b8c95 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cdd03482d481908b03d35dc2d16395 |
completed | April 2, 2026, 2:11 a.m. |
| PD | Predicate disambiguation | batch_69cd4b97870481908f7a89df10d58a9e |
completed | April 1, 2026, 4:45 p.m. |
Created at: March 30, 2026, 9 p.m.