Triple

T27477169
Position Surface form Disambiguated ID Type / Status
Subject Karkarduma metro station E693493 entity
Predicate interchangeBetween P21487 FINISHED
Object Blue Line and Pink Line
The Blue Line and Pink Line are two major corridors of the Delhi Metro network that intersect at Karkarduma metro station, facilitating passenger transfers between different parts of the city.
 E1791778 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: Blue Line and Pink Line | Statement: [Karkarduma metro station, interchangeBetween, Blue Line and Pink Line]
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: Blue Line and Pink Line
Triple: [Karkarduma metro station, interchangeBetween, Blue Line and Pink Line]
Generated description
The Blue Line and Pink Line are two major corridors of the Delhi Metro network that intersect at Karkarduma metro station, facilitating passenger transfers between different parts of the city.

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_69ef5381f2648190a2392d0fab833095 completed April 27, 2026, 12:16 p.m.
NER Named-entity recognition batch_69f62e451dd08190b9cbe3a9a2a4ffa6 completed May 2, 2026, 5:03 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12f702bcdc81909d3092dd1944f480 completed May 24, 2026, 1:02 p.m.
NEDg Description generation batch_6a12fb496c188190abbbcd5200aa5457 completed May 24, 2026, 1:21 p.m.
NED2 Entity disambiguation (via description) batch_6a12fbc87d94819097dbb89898b6ba03 completed May 24, 2026, 1:23 p.m.
Created at: April 27, 2026, 12:57 p.m.