Triple

T1835690
Position Surface form Disambiguated ID Type / Status
Subject Mercury Montego E41061 entity
Predicate manufacturer P490 FINISHED
Object Mercury E6367 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: Mercury | Statement: [Mercury Montego, manufacturer, Mercury]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mercury
Context triple: [Mercury Montego, manufacturer, Mercury]
  • A. Mercury chosen
    Mercury was an American automobile marque of the Ford Motor Company known for producing mid-priced cars positioned between Ford and Lincoln.
  • B. Mercury
    Mercury is the smallest and innermost planet in our Solar System, known for its extreme temperature variations and heavily cratered surface.
  • C. 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.
  • D. Venus
    Venus is the second planet from the Sun, known for its dense, toxic atmosphere, extreme surface temperatures, and bright visibility in Earth's sky.
  • E. Venus
    Venus is the Roman goddess of love, beauty, and fertility, often depicted as the divine ancestor and protector of Aeneas and the Roman people.
  • 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_69a88647f9388190909bc36e795bdaec completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb028226481908558c11449e1d6b6 completed March 7, 2026, 4:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69adfb9f3354819097ce858a8706c324 completed March 8, 2026, 10:43 p.m.
Created at: March 4, 2026, 7:33 p.m.