Triple

T17325394
Position Surface form Disambiguated ID Type / Status
Subject La Matanza Partido E420673 entity
Predicate hasLocality P7943 FINISHED
Object La Tablada
La Tablada is a working- and middle-class urban locality in Greater Buenos Aires, Argentina, known for its dense residential areas and industrial activity.
 E1263444 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: La Tablada | Statement: [La Matanza Partido, hasLocality, La Tablada]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Tablada
Context triple: [La Matanza Partido, hasLocality, La Tablada]
  • A. Barrio Bajo
    Barrio Bajo is the lower neighborhood district of Trévélez, a mountain village in Spain’s Alpujarras region.
  • B. La Plaza
    La Plaza is the historic central square of Los Angeles, recognized as the birthplace of the city and a focal point of its early civic and cultural life.
  • C. El Chorrillo
    El Chorrillo is a historic, densely populated neighborhood in Panama City, Panama, known for its working-class character and significant damage during the 1989 U.S. invasion.
  • D. El Realejo
    El Realejo is a historic coastal town and former colonial port in northwestern Nicaragua.
  • E. Suburra
    Suburra is a 2015 Italian crime film that explores the violent intersection of politics, organized crime, and real estate corruption in Rome.
  • 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: La Tablada
Triple: [La Matanza Partido, hasLocality, La Tablada]
Generated description
La Tablada is a working- and middle-class urban locality in Greater Buenos Aires, Argentina, known for its dense residential areas and industrial activity.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: La Tablada
Target entity description: La Tablada is a working- and middle-class urban locality in Greater Buenos Aires, Argentina, known for its dense residential areas and industrial activity.
  • A. Barrio Bajo
    Barrio Bajo is the lower neighborhood district of Trévélez, a mountain village in Spain’s Alpujarras region.
  • B. La Plaza
    La Plaza is the historic central square of Los Angeles, recognized as the birthplace of the city and a focal point of its early civic and cultural life.
  • C. El Chorrillo
    El Chorrillo is a historic, densely populated neighborhood in Panama City, Panama, known for its working-class character and significant damage during the 1989 U.S. invasion.
  • D. El Realejo
    El Realejo is a historic coastal town and former colonial port in northwestern Nicaragua.
  • E. Suburra
    Suburra is a 2015 Italian crime film that explores the violent intersection of politics, organized crime, and real estate corruption in Rome.
  • 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_69d889d3adc881909319f1edb8d2a956 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e439d24e548190a766dd246a4d63d4 completed April 19, 2026, 2:11 a.m.
NED1 Entity disambiguation (via context triple) batch_6a018c4c2dc08190b60982abc9ac7c9c completed May 11, 2026, 7:59 a.m.
NEDg Description generation batch_6a018f2358b481908226aa84a7bd9d7f completed May 11, 2026, 8:11 a.m.
NED2 Entity disambiguation (via description) batch_6a0190125abc8190ad4d1f500e3513b3 completed May 11, 2026, 8:15 a.m.
Created at: April 10, 2026, 5:43 a.m.