Triple
T9581910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mexico City Metrobús |
E231191
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
Line 4
Line 4 is a bus rapid transit route of the Mexico City Metrobús system that primarily serves the city’s historic center and connects it with key transport hubs, including the airport.
|
E43363
|
NE FINISHED |
How this triple was built (4 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 4 | Statement: [Mexico City Metrobús, hasLine, Line 4]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 4 Context triple: [Mexico City Metrobús, hasLine, Line 4]
-
A.
Line 4
Line 4 is a rapid transit route of the STC Metro system, serving as one of its main urban rail lines.
-
B.
Line 4
Line 4 is a proposed circular metro line intended to complete and expand the Seville Metro network in Seville, Spain.
-
C.
Line 4
Line 4 is a major line of the Santiago Metro in Chile, serving key residential and commercial areas in the southeastern part of the city.
-
D.
Line 4
Line 4 is a major north–south rapid transit route in the Beijing Subway system, serving key commercial, residential, and university areas of the city.
-
E.
Line 4
Line 4 is a planned rapid transit route within the future Ho Chi Minh City Metro system in Vietnam.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Line 4 Triple: [Mexico City Metrobús, hasLine, Line 4]
Generated description
Line 4 is a bus rapid transit route of the Mexico City Metrobús system that primarily serves the city’s historic center and connects it with key transport hubs, including the airport.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 4 Target entity description: Line 4 is a bus rapid transit route of the Mexico City Metrobús system that primarily serves the city’s historic center and connects it with key transport hubs, including the airport.
-
A.
Line 4
chosen
Line 4 is a route of Mexico City’s Metrobús bus rapid transit system that serves key corridors with dedicated lanes and high-capacity articulated buses.
-
B.
Line 4
Line 4 is a rapid transit route of the STC Metro system, serving as one of its main urban rail lines.
-
C.
Line 4
Line 4 is a rapid transit line of the Nanjing Metro system in Nanjing, China, serving as one of the city's main urban rail corridors.
-
D.
Line 4
Line 4 is a major north–south rapid transit route in the Beijing Subway system, serving key commercial, residential, and university areas of the city.
-
E.
Line 4
Line 4 is one of the main lines of the Tehran Metro rapid transit system, serving key east–west corridors across Iran’s capital city.
- F. None of above.
Provenance (5 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_69ca848161688190a68d514a0a9d5129 |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd99cd59008190888eb11f00f61994 |
completed | April 1, 2026, 10:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1616a11688190ba47343e4fd913fd |
completed | April 4, 2026, 7:07 p.m. |
| NEDg | Description generation | batch_69d16360b7708190bc23294f267ac695 |
completed | April 4, 2026, 7:15 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69d163e654388190ba9b617e6fac18ad |
completed | April 4, 2026, 7:17 p.m. |
Created at: March 30, 2026, 8:05 p.m.