Triple

T4146383
Position Surface form Disambiguated ID Type / Status
Subject Marella Ciano E89792 entity
Predicate givenName P17 FINISHED
Object Marella
Marella is an Italian feminine given name, notably borne by Marella Agnelli, a prominent socialite, art collector, and style icon.
 E414817 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: Marella | Statement: [Marella Ciano, givenName, Marella]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marella
Context triple: [Marella Ciano, givenName, Marella]
  • A. Mara
    Mara is a surname of Irish origin borne by various notable individuals in fields such as sports, entertainment, and politics.
  • B. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • C. Adara
    Adara is a small coastal village on Atauro Island in East Timor, known for its traditional fishing community and nearby coral reefs popular with divers and snorkelers.
  • D. Mella
    Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
  • E. Ephyra
    Ephyra is an ancient city in Greek mythology, often identified with Corinth and known as the legendary home of King Sisyphus.
  • 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: Marella
Triple: [Marella Ciano, givenName, Marella]
Generated description
Marella is an Italian feminine given name, notably borne by Marella Agnelli, a prominent socialite, art collector, and style icon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marella
Target entity description: Marella is an Italian feminine given name, notably borne by Marella Agnelli, a prominent socialite, art collector, and style icon.
  • A. Mara
    Mara is a surname of Irish origin borne by various notable individuals in fields such as sports, entertainment, and politics.
  • B. Mylasa
    Mylasa was an important ancient city of Caria in southwestern Anatolia, known as a political and religious center, particularly for the worship of Zeus.
  • C. Adara
    Adara is a small coastal village on Atauro Island in East Timor, known for its traditional fishing community and nearby coral reefs popular with divers and snorkelers.
  • D. Mella
    Mella is a Spanish-language surname most notably associated with Cuban revolutionary leader Julio Antonio Mella.
  • E. Ephyra
    Ephyra is an ancient city in Greek mythology, often identified with Corinth and known as the legendary home of King Sisyphus.
  • 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_69aed95a59a881909b26e70b42c6811a completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af025fef088190b42515d0a854a1ae completed March 9, 2026, 5:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69b576d5379081908300afbb3a6fe5e4 completed March 14, 2026, 2:55 p.m.
NEDg Description generation batch_69b577c2b784819096d8218dd1c1478d completed March 14, 2026, 2:59 p.m.
NED2 Entity disambiguation (via description) batch_69b5782cc448819080e306952da24ac0 completed March 14, 2026, 3:01 p.m.
Created at: March 9, 2026, 3:43 p.m.