Triple

T9517612
Position Surface form Disambiguated ID Type / Status
Subject Koura District E229563 entity
Predicate hasTown P847 FINISHED
Object Barsa
Barsa is a town located in the Koura District of northern Lebanon.
E806972 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: Barsa | Statement: [Koura District, hasTown, Barsa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Barsa
Context triple: [Koura District, hasTown, Barsa]
  • A. Barakaldo
    Barakaldo is a major industrial and residential city in the Basque Country in northern Spain, located near Bilbao along the Nervión River.
  • B. Bilbao
    Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
  • C. Bilbao
    Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
  • D. Zaragoza
    Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
  • E. Zaragoza
    Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
  • 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: Barsa
Triple: [Koura District, hasTown, Barsa]
Generated description
Barsa is a town located in the Koura District of northern Lebanon.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Barsa
Target entity description: Barsa is a town located in the Koura District of northern Lebanon.
  • A. Barakaldo
    Barakaldo is a major industrial and residential city in the Basque Country in northern Spain, located near Bilbao along the Nervión River.
  • B. Bilbao
    Bilbao is a station on Madrid's Metro network, serving Line 1 and located in the central Chamberí district.
  • C. Bilbao
    Bilbao is a major port city in northern Spain renowned for its industrial heritage, cultural institutions like the Guggenheim Museum, and role as an economic hub of the Basque Country.
  • D. Zaragoza
    Zaragoza is a historic city in northeastern Spain, known for landmarks like the Basilica del Pilar and its role as a major cultural and economic center in the Aragon region.
  • E. Zaragoza
    Zaragoza is a metro station on Mexico City’s Line 1 that serves as a key eastern access point to the city’s rapid transit network.
  • 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_69ca84777560819084cddd999badc1aa completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cd9880417c819097dde277988df36d completed April 1, 2026, 10:13 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1526fbad8819099dfae3b7226898b completed April 4, 2026, 6:03 p.m.
NEDg Description generation batch_69d154f32b28819084cfe2482e89cab0 completed April 4, 2026, 6:14 p.m.
NED2 Entity disambiguation (via description) batch_69d1556753dc81908fbfdc7b863b1026 completed April 4, 2026, 6:16 p.m.
Created at: March 30, 2026, 7:59 p.m.