Triple
T1768697
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Shanghai Metro |
E38822
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object | Line 9 |
E188953
|
NE 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: Line 9 | Statement: [Shanghai Metro, hasLine, Line 9]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 9 Context triple: [Shanghai Metro, hasLine, Line 9]
-
A.
Line 9
Line 9 is a line of the Mexico City Metro system that serves as one of its key rapid transit routes across the city.
-
B.
Line 9
chosen
Line 9 is a rapid transit line of the Guangzhou Metro system serving parts of Guangzhou, China.
-
C.
Line 9
Line 9 is a rapid transit line of the Beijing Subway system that serves as part of the city's urban rail network.
-
D.
Line 8
Line 8 is a route of Mexico City’s Metrobús bus rapid transit system, serving key corridors with dedicated lanes and station platforms.
-
E.
Line 8
Line 8 is a line of the Mexico City Metro system that runs in a generally north–south direction, connecting key residential and commercial areas of the city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa648d9f2c8190aca4884648a69eb0 |
completed | March 6, 2026, 5:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adc9a14a18819090b83b3d10304c74 |
completed | March 8, 2026, 7:10 p.m. |
Created at: March 4, 2026, 7:31 p.m.