Triple

T13553399
Position Surface form Disambiguated ID Type / Status
Subject MTM E323704 entity
Predicate targetBody P860 FINISHED
Object planet Mercury E1051357 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: planet Mercury | Statement: [MTM, targetBody, planet Mercury]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: planet Mercury
Context triple: [MTM, targetBody, planet Mercury]
  • A. planet Mercury chosen
    Planet Mercury is the smallest and innermost planet in the Solar System, known for its extreme temperature variations and rapid 88-day orbit around the Sun.
  • B. Merkur
    Merkur was a short-lived automotive marque created by Ford in the 1980s to sell European-designed performance and luxury cars in the North American market.
  • C. Mercuri
    Mercuri is the surname of Brazilian singer, songwriter, and performer Daniela Mercury, a prominent figure in axé and pop music.
  • D. Mercury
    Mercury was an American automobile marque of the Ford Motor Company known for producing mid-priced cars positioned between Ford and Lincoln.
  • E. Mercury
    Mercury is the Roman god of commerce, communication, and travel, often depicted as a swift messenger of the gods.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbaff1c1f0819084352d9b2ee13d7a completed April 12, 2026, 2:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69f79d3d860c8190a166666a20971de7 completed May 3, 2026, 7:08 p.m.
Created at: April 9, 2026, 9:46 p.m.