Triple

T16169109
Position Surface form Disambiguated ID Type / Status
Subject Temples of Venus E392386 entity
Predicate dedicatedTo P500 FINISHED
Object Venus E116817 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: Venus | Statement: [Temples of Venus, dedicatedTo, Venus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Venus
Context triple: [Temples of Venus, dedicatedTo, Venus]
  • A. Venus
    Venus is a character in the action film "Crank: High Voltage," known for her involvement in the movie’s chaotic, high-energy storyline.
  • B. 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.
  • C. Venus chosen
    Venus is the Roman goddess of love, beauty, and fertility, often depicted as the divine ancestor and protector of Aeneas and the Roman people.
  • D. Venus
    Venus is a small suburban town within the greater Dallas–Fort Worth metropolitan area in Texas.
  • E. Venus
    Venus is a Romanian Black Sea seaside resort town in Constanța County, known for its beaches and tourism.
  • 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_69d87f1d32208190942e4e499a80c18c completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e21eb5e6d881908749683091afa90c completed April 17, 2026, 11:51 a.m.
NED1 Entity disambiguation (via context triple) batch_69fff7bb6aac8190a33607abfe9a32d0 completed May 10, 2026, 3:12 a.m.
Created at: April 10, 2026, 5:02 a.m.