Triple
T7798214
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Red Line (Delhi Metro) |
E180354
|
entity |
| Predicate | lineNumber |
P1864
|
FINISHED |
| Object |
Line 1
Line 1 is the designation for the Red Line, one of the main rapid transit corridors of the Delhi Metro network in India.
|
E694099
|
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 1 | Statement: [Red Line (Delhi Metro), lineNumber, Line 1]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Line 1 Context triple: [Red Line (Delhi Metro), lineNumber, Line 1]
-
A.
Line 1
Line 1 is the oldest and one of the busiest lines of the Santiago Metro, running primarily east–west across central Santiago, Chile.
-
B.
Line 1
Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
-
C.
Line 1
Line 1 is the oldest and one of the busiest lines of the Mexico City Metro, running east–west across the city and serving many central, high-traffic stations.
-
D.
Line 1
Line 1 is a major rapid transit line of the Guangzhou Metro system in Guangzhou, China, serving as one of the city's primary east–west corridors.
-
E.
Line 1
Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest routes.
- 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 1 Triple: [Red Line (Delhi Metro), lineNumber, Line 1]
Generated description
Line 1 is the designation for the Red Line, one of the main rapid transit corridors of the Delhi Metro network in India.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Line 1 Target entity description: Line 1 is the designation for the Red Line, one of the main rapid transit corridors of the Delhi Metro network in India.
-
A.
Line 1
Line 1 is the first operational corridor of the Mumbai Monorail system, serving as a key elevated transit route in Mumbai, India.
-
B.
Line 1
Line 1 is the numerical designation commonly used for Ottawa’s Confederation Line, the city’s primary light rail transit route.
-
C.
Line 1
Line 1 is one of the main east–west rapid transit lines of the Beijing Subway, serving as a core corridor through central Beijing.
-
D.
Line 1
Line 1 is a major line of the Seoul Metropolitan Subway system, serving as one of its oldest and busiest commuter rail corridors across the Seoul metropolitan area.
-
E.
Line 1
Line 1 is a major north–south rapid transit line of the Shanghai Metro and one of the system’s oldest and busiest routes.
- F. None of above. chosen
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_69ca827d22208190b4dc5aa680edcf5d |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cae984185881908117f9f549ffc443 |
completed | March 30, 2026, 9:22 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb14149abc8190b172cfa8ab3b0fba |
completed | March 31, 2026, 12:23 a.m. |
| NEDg | Description generation | batch_69cb1636b0d48190a57c2d3a7b3b41ed |
completed | March 31, 2026, 12:32 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb1a3e6da08190bf4f82b59db41333 |
completed | March 31, 2026, 12:50 a.m. |
Created at: March 30, 2026, 4:32 p.m.