Triple
T6281414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 12 (MetroSur) |
E140789
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object |
MetroSur
MetroSur is a circular suburban line of the Madrid Metro that connects several southern municipalities of the Madrid metropolitan area.
|
E581234
|
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: MetroSur | Statement: [Line 12 (MetroSur), name, MetroSur]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: MetroSur Context triple: [Line 12 (MetroSur), name, MetroSur]
-
A.
Metros
Metros is the nickname historically used for the MetroStars, the former Major League Soccer team now known as the New York Red Bulls.
-
B.
Metro Cebu
Metro Cebu is the main metropolitan area of Cebu in the Philippines, encompassing Cebu City and its surrounding cities and municipalities as a major economic, cultural, and transportation hub in the Visayas region.
-
C.
METRO
METRO is the public-facing brand name used by Metro Transit for its network of buses, trains, and other mass transportation services.
-
D.
Muni
Muni is San Francisco’s primary public transit agency, operating buses, light rail, historic streetcars, and the city’s iconic cable cars.
-
E.
Muni
Muni is an honorific title traditionally used in Indian culture to denote a sage, seer, or revered spiritual teacher.
- 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: MetroSur Triple: [Line 12 (MetroSur), name, MetroSur]
Generated description
MetroSur is a circular suburban line of the Madrid Metro that connects several southern municipalities of the Madrid metropolitan area.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: MetroSur Target entity description: MetroSur is a circular suburban line of the Madrid Metro that connects several southern municipalities of the Madrid metropolitan area.
-
A.
Metros
Metros is the nickname historically used for the MetroStars, the former Major League Soccer team now known as the New York Red Bulls.
-
B.
Metro Cebu
Metro Cebu is the main metropolitan area of Cebu in the Philippines, encompassing Cebu City and its surrounding cities and municipalities as a major economic, cultural, and transportation hub in the Visayas region.
-
C.
METRO
METRO is the public-facing brand name used by Metro Transit for its network of buses, trains, and other mass transportation services.
-
D.
Muni
Muni is San Francisco’s primary public transit agency, operating buses, light rail, historic streetcars, and the city’s iconic cable cars.
-
E.
Muni
Muni is an honorific title traditionally used in Indian culture to denote a sage, seer, or revered spiritual teacher.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063dee62881908347283f16dcbe68 |
completed | March 22, 2026, 9:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c51962132881909a2eccd1203e03c1 |
completed | March 26, 2026, 11:32 a.m. |
| NEDg | Description generation | batch_69c51b4803e08190ac067896da3400e5 |
completed | March 26, 2026, 11:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c51bf81cfc8190a6f0e4ca74c7ff05 |
completed | March 26, 2026, 11:43 a.m. |
Created at: March 22, 2026, 4:26 p.m.