Triple

T16792605
Position Surface form Disambiguated ID Type / Status
Subject Arganzuela E408147 entity
Predicate hasNeighbouringDistrict P17964 FINISHED
Object Usera
Usera is a district in the south of Madrid, Spain, known as a largely residential area with a diverse, working-class population.
 E1233234 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: Usera | Statement: [Arganzuela, hasNeighbouringDistrict, Usera]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Usera
Context triple: [Arganzuela, hasNeighbouringDistrict, Usera]
  • A. Ula
    Ula is a character connected to the life and experiences depicted in Henry Roth’s semi-autobiographical writings.
  • B. Ula
    Ula is a small town and district in southwestern Turkey known for its traditional architecture and proximity to the coastal resorts of the Aegean region.
  • C. Kuser
    Kuser is a surname associated with an American family notable in New Jersey politics, business, and public life in the late 19th and early 20th centuries.
  • D. Ukiel
    Ukiel is a prominent lake near the city of Olsztyn in northern Poland, known for its recreational opportunities and scenic surroundings.
  • E. Uzeste
    Uzeste is a small commune in southwestern France notable for its historic church that houses the tomb of Pope Clement V.
  • 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: Usera
Triple: [Arganzuela, hasNeighbouringDistrict, Usera]
Generated description
Usera is a district in the south of Madrid, Spain, known as a largely residential area with a diverse, working-class population.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Usera
Target entity description: Usera is a district in the south of Madrid, Spain, known as a largely residential area with a diverse, working-class population.
  • A. Ula
    Ula is a character connected to the life and experiences depicted in Henry Roth’s semi-autobiographical writings.
  • B. Ula
    Ula is a small town and district in southwestern Turkey known for its traditional architecture and proximity to the coastal resorts of the Aegean region.
  • C. Kuser
    Kuser is a surname associated with an American family notable in New Jersey politics, business, and public life in the late 19th and early 20th centuries.
  • D. Ukiel
    Ukiel is a prominent lake near the city of Olsztyn in northern Poland, known for its recreational opportunities and scenic surroundings.
  • E. Uzeste
    Uzeste is a small commune in southwestern France notable for its historic church that houses the tomb of Pope Clement V.
  • 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_69d88393905081908d00a86b99996ac8 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b2a7817c8190a53d0cfb5ef66a71 completed April 18, 2026, 4:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00ab0e1e9c8190bb2ef0825b25f6e5 completed May 10, 2026, 3:58 p.m.
NEDg Description generation batch_6a00ac1d18c08190969108e567d6eced completed May 10, 2026, 4:02 p.m.
NED2 Entity disambiguation (via description) batch_6a00acc658f881908db64ebfa5a86f84 completed May 10, 2026, 4:05 p.m.
Created at: April 10, 2026, 5:22 a.m.