Triple
T7842514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yellow Line (Delhi Metro) |
E181839
|
entity |
| Predicate | hasStation |
P35
|
FINISHED |
| Object |
Green Park
Green Park is a Delhi Metro station in South Delhi serving the Green Park and nearby Hauz Khas and Safdarjung areas.
|
E705829
|
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: Green Park | Statement: [Yellow Line (Delhi Metro), hasStation, Green Park]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Green Park Context triple: [Yellow Line (Delhi Metro), hasStation, Green Park]
-
A.
Green Park
Green Park is a central London royal park known for its open lawns, mature trees, and tranquil atmosphere between Buckingham Palace and Piccadilly.
-
B.
Green Park
Green Park is a public park in Kanpur, India, historically significant enough to lend its name to the nearby Green Park Stadium.
-
C.
Grosvenor Park
Grosvenor Park is a large Victorian-era public park in Chester, England, known for its formal gardens, riverside setting, and historic features.
-
D.
Holland Park
Holland Park is a leafy, affluent district and public park in west London known for its elegant townhouses, landscaped gardens, and cultural attractions.
-
E.
Old Kent Park
Old Kent Park was the original name of the minor league baseball stadium now known as LMCU Ballpark, home of the West Michigan Whitecaps.
- 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: Green Park Triple: [Yellow Line (Delhi Metro), hasStation, Green Park]
Generated description
Green Park is a Delhi Metro station in South Delhi serving the Green Park and nearby Hauz Khas and Safdarjung areas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Green Park Target entity description: Green Park is a Delhi Metro station in South Delhi serving the Green Park and nearby Hauz Khas and Safdarjung areas.
-
A.
Green Park
Green Park is a central London royal park known for its open lawns, mature trees, and tranquil atmosphere between Buckingham Palace and Piccadilly.
-
B.
Green Park
Green Park is a public park in Kanpur, India, historically significant enough to lend its name to the nearby Green Park Stadium.
-
C.
Grosvenor Park
Grosvenor Park is a large Victorian-era public park in Chester, England, known for its formal gardens, riverside setting, and historic features.
-
D.
Holland Park
Holland Park is a leafy, affluent district and public park in west London known for its elegant townhouses, landscaped gardens, and cultural attractions.
-
E.
Old Kent Park
Old Kent Park was the original name of the minor league baseball stadium now known as LMCU Ballpark, home of the West Michigan Whitecaps.
- 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_69ca8285d6488190a95d4c02d7354b53 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb163b32688190b463a9cd8fa3c690 |
completed | March 31, 2026, 12:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc55fe5b4c8190b35ddbef8c372269 |
completed | March 31, 2026, 11:17 p.m. |
| NEDg | Description generation | batch_69cc5822581481908a143376bee599ec |
completed | March 31, 2026, 11:26 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69cc58f549388190ba6c8b41c0820cd6 |
completed | March 31, 2026, 11:29 p.m. |
Created at: March 30, 2026, 4:48 p.m.