Triple

T8516052
Position Surface form Disambiguated ID Type / Status
Subject Kaa E201573 entity
Predicate species P87 FINISHED
Object Indian python E275886 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: Indian python | Statement: [Kaa, species, Indian python]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Indian python
Context triple: [Kaa, species, Indian python]
  • A. Indian python chosen
    The Indian python is a large, nonvenomous constrictor snake native to the Indian subcontinent, typically found in forests, grasslands, and wetlands.
  • B. Burmese python
    The Burmese python is a large, nonvenomous constrictor snake native to Southeast Asia that has become a highly destructive invasive species in the Florida Everglades.
  • C. Nyctophilopython
    Nyctophilopython is a genus of pythons, a group of nonvenomous constrictor snakes within the family Pythonidae.
  • D. Víbora
    Víbora is a traditional residential neighborhood in Havana, Cuba, known for its dense urban fabric and local commercial activity.
  • E. Leiopython
    Leiopython is a small genus of nonvenomous pythons native to New Guinea, commonly known as white-lipped pythons for their distinctive pale upper lip scales.
  • 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe60f37b0819082ae14e539f57b56 completed March 31, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce4e5dbb3c81909157e6b04a4956af completed April 2, 2026, 11:09 a.m.
Created at: March 30, 2026, 6:15 p.m.