Triple

T15356355
Position Surface form Disambiguated ID Type / Status
Subject Guardians of the Galaxy Vol. 2 E367175 entity
Predicate character P662 FINISHED
Object Groot E199167 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: Groot | Statement: [Guardians of the Galaxy Vol. 2, character, Groot]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Groot
Context triple: [Guardians of the Galaxy Vol. 2, character, Groot]
  • A. Groot chosen
    Groot is a sentient, tree-like alien superhero from Marvel Comics and the Marvel Cinematic Universe, known for his limited vocabulary and close partnership with Rocket Raccoon.
  • B. Baiju
    Baiju was a 13th-century Mongol general who led Mongol forces in their campaigns into Eastern Europe.
  • C. Banzi
    Banzi is a town in the Basilicata region of southern Italy, known as the modern site near the ancient Lucanian city of Bantia.
  • D. Padirac Chasm
    Padirac Chasm is a famous limestone sinkhole and underground cave system in southwestern France, renowned for its vast subterranean galleries and boat-accessible river.
  • E. Rocket Raccoon
    Rocket Raccoon is a genetically modified, cybernetically enhanced raccoon-like creature known for his sharpshooting skills, engineering genius, and sarcastic wit in the Marvel universe.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e2c00648190ae2325e1ee58dcfd completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff02012fa48190a108f1ca710ffb15 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:18 a.m.