Triple

T7798240
Position Surface form Disambiguated ID Type / Status
Subject Red Line (Delhi Metro) E180354 entity
Predicate hasStation P35 FINISHED
Object Rithala E694100 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: Rithala | Statement: [Red Line (Delhi Metro), hasStation, Rithala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Rithala
Context triple: [Red Line (Delhi Metro), hasStation, Rithala]
  • A. Rithala chosen
    Rithala is a metro station in Delhi, India, serving as the northern endpoint of the Delhi Metro’s Red Line and a key transit hub for the surrounding residential and commercial areas.
  • B. Barnala
    Barnala is a city in the Malwa region of Punjab, India, known as an administrative and commercial center for the surrounding agricultural area.
  • C. Randhawa
    Randhawa is an Indian-origin Punjabi surname notably borne by American politician Nikki Haley.
  • D. Nawanshahr
    Nawanshahr is a town and district headquarters in the Doaba region of Punjab, India, known for its agricultural base and significant Punjabi diaspora.
  • E. Phagwara
    Phagwara is a prominent industrial and commercial city in the Indian state of Punjab, known for its textile and agricultural machinery industries and its location on the major highway between Ludhiana and Jalandhar.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69cb5a18014c8190be64130bfb856e10 completed March 31, 2026, 5:22 a.m.
Created at: March 30, 2026, 4:32 p.m.