Triple

T3244023
Position Surface form Disambiguated ID Type / Status
Subject Procter & Gamble E68029 entity
Predicate hasBrand P1500 FINISHED
Object Venus
Venus is a Procter & Gamble personal care brand best known for its women's razors and shaving products.
 E342344 NE FINISHED

How this triple was built (4 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: [Procter & Gamble, hasBrand, Venus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Venus
Context triple: [Procter & Gamble, hasBrand, Venus]
  • A. 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.
  • B. 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.
  • C. Venus
    "Venus" is a 2006 British comedy-drama film directed by Roger Michell, starring Peter O'Toole as an aging actor whose life is shaken up by his unexpected relationship with a young woman.
  • D. Venus and Mars
    "Venus and Mars" is a 1975 rock album by Paul McCartney and Wings, known for its melodic pop-rock style and serving as the follow-up to the hugely successful "Band on the Run."
  • E. 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.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Venus
Triple: [Procter & Gamble, hasBrand, Venus]
Generated description
Venus is a Procter & Gamble personal care brand best known for its women's razors and shaving products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Venus
Target entity description: Venus is a Procter & Gamble personal care brand best known for its women's razors and shaving products.
  • A. 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.
  • B. 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.
  • C. Venus
    "Venus" is a 2006 British comedy-drama film directed by Roger Michell, starring Peter O'Toole as an aging actor whose life is shaken up by his unexpected relationship with a young woman.
  • D. Venus and Mars
    "Venus and Mars" is a 1975 rock album by Paul McCartney and Wings, known for its melodic pop-rock style and serving as the follow-up to the hugely successful "Band on the Run."
  • E. 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.
  • F. None of above. chosen

Provenance (5 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_69ad858e4c708190aa31d486cfee8a6a completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf1856708190b072efbb27920ade completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28eb55734819093f470caacc3e29c completed March 12, 2026, 10 a.m.
NEDg Description generation batch_69b28f9e12488190b93355b783300264 completed March 12, 2026, 10:04 a.m.
NED2 Entity disambiguation (via description) batch_69b2c092063481909982dea3f71c00c1 completed March 12, 2026, 1:33 p.m.
Created at: March 8, 2026, 3:08 p.m.