Triple

T1011478
Position Surface form Disambiguated ID Type / Status
Subject The Ten Commandments (1956 film) E21832 entity
Predicate character P662 FINISHED
Object Sephora
Sephora is a character in the 1956 biblical epic film "The Ten Commandments," depicted as Moses' Midianite wife Zipporah.
 E120822 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: Sephora | Statement: [The Ten Commandments (1956 film), character, Sephora]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Sephora
Context triple: [The Ten Commandments (1956 film), character, Sephora]
  • A. Bath & Body Works
    Bath & Body Works is a major American retail chain specializing in scented personal care products, candles, and home fragrances, known for its mall-based stores and seasonal collections.
  • B. Kiehl's
    Kiehl's is an American skincare and cosmetics brand known for its apothecary-style stores and science-driven formulations.
  • C. Lancôme
    Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
  • D. Clinique
    Clinique is an American skincare and cosmetics brand known for its dermatologist-developed, fragrance-free products and clinical approach to beauty.
  • E. Yves Saint Laurent Beauté
    Yves Saint Laurent Beauté is a luxury cosmetics and fragrance brand known for its high-end makeup, skincare, and iconic perfumes.
  • 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: Sephora
Triple: [The Ten Commandments (1956 film), character, Sephora]
Generated description
Sephora is a character in the 1956 biblical epic film "The Ten Commandments," depicted as Moses' Midianite wife Zipporah.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Sephora
Target entity description: Sephora is a character in the 1956 biblical epic film "The Ten Commandments," depicted as Moses' Midianite wife Zipporah.
  • A. Bath & Body Works
    Bath & Body Works is a major American retail chain specializing in scented personal care products, candles, and home fragrances, known for its mall-based stores and seasonal collections.
  • B. Kiehl's
    Kiehl's is an American skincare and cosmetics brand known for its apothecary-style stores and science-driven formulations.
  • C. Lancôme
    Lancôme is a French luxury cosmetics and skincare brand renowned for its high-end perfumes, makeup, and beauty products.
  • D. Clinique
    Clinique is an American skincare and cosmetics brand known for its dermatologist-developed, fragrance-free products and clinical approach to beauty.
  • E. Yves Saint Laurent Beauté
    Yves Saint Laurent Beauté is a luxury cosmetics and fragrance brand known for its high-end makeup, skincare, and iconic perfumes.
  • 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_69a493c68e24819080ed0ee8bcfd5ce0 completed March 1, 2026, 7:30 p.m.
NER Named-entity recognition batch_69a4b7a743cc8190a46e6a14e3e8130f completed March 1, 2026, 10:03 p.m.
NED1 Entity disambiguation (via context triple) batch_69ac3bab71388190ba8bbfd79a5e0f92 completed March 7, 2026, 2:52 p.m.
NEDg Description generation batch_69ac3c30311081909e817de7cf9c2d9b completed March 7, 2026, 2:54 p.m.
NED2 Entity disambiguation (via description) batch_69ac3c9cc1ec819087df1f4c4efc5646 completed March 7, 2026, 2:56 p.m.
Created at: March 1, 2026, 7:41 p.m.