Triple

T13049323
Position Surface form Disambiguated ID Type / Status
Subject Mery Andrade E327407 entity
Predicate givenName P17 FINISHED
Object Mery
Mery is the given name of Mery Andrade, a Venezuelan former professional basketball player and coach.
 E1017257 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: Mery | Statement: [Mery Andrade, givenName, Mery]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Mery
Context triple: [Mery Andrade, givenName, Mery]
  • A. Mere
    Mere is a small historic market town in southwest Wiltshire, England, known for its rural setting near the borders of Dorset and Somerset.
  • B. Mere
    Mere is a village and civil parish in Cheshire, England, known for its affluent residential character and proximity to the town of Knutsford.
  • C. Maren
    Maren is a feminine given name of Scandinavian origin, commonly used in Norway and Denmark.
  • D. Megyn
    Megyn is a feminine given name most prominently associated with American journalist and television personality Megyn Kelly.
  • E. Marya
    Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
  • 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: Mery
Triple: [Mery Andrade, givenName, Mery]
Generated description
Mery is the given name of Mery Andrade, a Venezuelan former professional basketball player and coach.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Mery
Target entity description: Mery is the given name of Mery Andrade, a Venezuelan former professional basketball player and coach.
  • A. Mere
    Mere is a small historic market town in southwest Wiltshire, England, known for its rural setting near the borders of Dorset and Somerset.
  • B. Mere
    Mere is a village and civil parish in Cheshire, England, known for its affluent residential character and proximity to the town of Knutsford.
  • C. Maren
    Maren is a feminine given name of Scandinavian origin, commonly used in Norway and Denmark.
  • D. Megyn
    Megyn is a feminine given name most prominently associated with American journalist and television personality Megyn Kelly.
  • E. Marya
    Marya is a feminine given name, often considered a variant of Mary and used in various cultures and languages.
  • 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_69d8076e64308190904fb5c93517c901 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d980b8811c81908577f092e2736610 completed April 10, 2026, 10:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6cbda9b548190a10a4835b2c75fdc completed May 3, 2026, 4:15 a.m.
NEDg Description generation batch_69f6cd0d21e08190855dcbee000fc25d completed May 3, 2026, 4:20 a.m.
NED2 Entity disambiguation (via description) batch_69f6ce6b220c8190b1f49a9b2bfce692 completed May 3, 2026, 4:26 a.m.
Created at: April 9, 2026, 8:57 p.m.