Triple

T14026198
Position Surface form Disambiguated ID Type / Status
Subject Landour E337462 entity
Predicate hasLandmark P105 FINISHED
Object Lal Tibba E337459 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: Lal Tibba | Statement: [Landour, hasLandmark, Lal Tibba]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lal Tibba
Context triple: [Landour, hasLandmark, Lal Tibba]
  • A. Lal Tibba chosen
    Lal Tibba is a popular scenic viewpoint in Mussoorie, India, known for its panoramic Himalayan mountain vistas.
  • B. Kabir Chabutra
    Kabir Chabutra is a revered spiritual site near Amarkantak, associated with the 15th-century mystic poet-saint Kabir and visited by pilgrims for meditation and reflection.
  • C. Shikharji
    Shikharji is one of the holiest pilgrimage sites in Jainism, revered as the place where many Jain Tirthankaras are believed to have attained moksha.
  • D. Mata Tripta
    Mata Tripta was the mother of Guru Nanak, the founder of Sikhism, and is revered in Sikh tradition for her piety and nurturing role in his early life.
  • E. Chander Pahar
    Chander Pahar is a classic Bengali adventure novel that follows a young man's perilous explorations in the wilds of Africa.
  • 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_69d81c6543a48190bd5ba93d7419e797 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de2fa6ca7481908976ce748a1957b1 completed April 14, 2026, 12:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69fbc333b7a08190b4f121fef69f7513 completed May 6, 2026, 10:39 p.m.
Created at: April 9, 2026, 10:20 p.m.