Triple

T15609040
Position Surface form Disambiguated ID Type / Status
Subject Pangong Tso E375237 entity
Predicate alsoKnownAs P39 FINISHED
Object Pangong Lake E375237 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: Pangong Lake | Statement: [Pangong Tso, alsoKnownAs, Pangong Lake]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pangong Lake
Context triple: [Pangong Tso, alsoKnownAs, Pangong Lake]
  • A. Pangong Tso chosen
    Pangong Tso is a high-altitude, endorheic lake in the Himalayas, famed for its striking blue waters and location along the disputed border between India and China.
  • B. Pichola Lake
    Pichola Lake is a picturesque artificial freshwater lake in Udaipur, Rajasthan, famed for its island palaces, surrounding ghats, and scenic views of the Aravalli hills.
  • C. Lakha Banjara Lake
    Lakha Banjara Lake is a prominent artificial lake and local landmark situated near the city of Sagar in Madhya Pradesh, India.
  • D. Sukhna Lake
    Sukhna Lake is a man-made reservoir at the foothills of the Shivalik range, known as a popular recreational and scenic spot in Chandigarh, India.
  • E. Rawal Lake
    Rawal Lake is an artificial reservoir and popular recreational spot located near Islamabad in Pakistan’s Margalla Hills foothills.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e8024948190a6c711f2e5c2aac4 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f37383c81909d0efce84508a034 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:13 a.m.