Triple

T3242318
Position Surface form Disambiguated ID Type / Status
Subject Lake Bolsena E67989 entity
Predicate hasShore P969 FINISHED
Object Marta
Marta is a small Italian town in the Lazio region, situated on the southern shore of Lake Bolsena and known for its lakeside scenery and historic center.
 E342328 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: Marta | Statement: [Lake Bolsena, hasShore, Marta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Marta
Context triple: [Lake Bolsena, hasShore, Marta]
  • A. Marta
    Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
  • B. Marta
    Marta is a legendary Brazilian footballer widely regarded as one of the greatest women’s players of all time.
  • C. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • D. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • 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: Marta
Triple: [Lake Bolsena, hasShore, Marta]
Generated description
Marta is a small Italian town in the Lazio region, situated on the southern shore of Lake Bolsena and known for its lakeside scenery and historic center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Marta
Target entity description: Marta is a small Italian town in the Lazio region, situated on the southern shore of Lake Bolsena and known for its lakeside scenery and historic center.
  • A. Marta
    Marta is a feminine given name commonly used in many European and Latin American countries, often considered a variant of the name Martha.
  • B. Marta
    Marta is a legendary Brazilian footballer widely regarded as one of the greatest women’s players of all time.
  • C. María
    "María" is a film featuring actress Taryn Power in a significant role.
  • D. María
    María is a key character in Ernest Hemingway's novel "For Whom the Bell Tolls," known as a young Spanish woman and love interest of the protagonist amid the Spanish Civil War.
  • E. Paola
    Paola is an Italian noblewoman who became Queen consort of Belgium as the wife of King Albert II.
  • 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_69ad858d27348190abb61c280b4c86a9 completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69adaf17463481909447f6ab46016407 completed March 8, 2026, 5:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b28eadeff481909bd48cdf51044f86 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.