Triple
T14887070
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chaoyangmen station |
E359654
|
entity |
| Predicate | line |
P1293
|
FINISHED |
| Object | Line 6 |
E451279
|
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 6 | Statement: [Chaoyangmen station, line, Line 6]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 6 Context triple: [Chaoyangmen station, line, Line 6]
-
A.
Line 6
Line 6 is a route of Mexico City’s Metrobús bus rapid transit system that serves as one of the network’s main corridors.
-
B.
Line 6
Line 6 is a rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving multiple urban districts with frequent subway service.
-
C.
Line 6
Line 6 is a Culver CityBus route in the Los Angeles area that provides local and regional public transit service connecting key neighborhoods and transit hubs.
-
D.
Line 6
chosen
Line 6 is a rapid transit line of the Shenzhen Metro system in Shenzhen, China, serving multiple districts across the city.
-
E.
Line 6
Line 6 is one of the lines of the Paris Métro, known for its largely elevated route offering views of the city, including the Eiffel Tower.
- 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_69d827980cbc8190a0c569ae3940a1d9 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69ded5f5b1c88190815f3585770cb135 |
completed | April 15, 2026, 12:04 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe6b5f22c08190a9530cbd78cfc801 |
completed | May 8, 2026, 11:01 p.m. |
Created at: April 10, 2026, 2:07 a.m.