Triple

T8932894
Position Surface form Disambiguated ID Type / Status
Subject Bong County E212699 entity
Predicate hasTown P847 FINISHED
Object Salala
Salala is a town in central Liberia that serves as an important local hub within Bong County.
E767823 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: Salala | Statement: [Bong County, hasTown, Salala]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Salala
Context triple: [Bong County, hasTown, Salala]
  • A. Salayea
    Salayea is a town in northwestern Liberia located within Lofa County.
  • B. Salora
    Salora was a prominent Finnish electronics manufacturer best known for producing televisions and radios, and it played a key role in the industrial history of Salo, Finland.
  • C. Lalsalu
    Lalsalu is a classic Bengali novel by Syed Waliullah that explores religious hypocrisy and rural life in East Bengal.
  • D. Kalsa
    Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
  • E. Lasbela
    Lasbela is a coastal district and city in Pakistan’s Balochistan province, known for its strategic location near Karachi and its mix of industrial, agricultural, and fishing activities.
  • 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: Salala
Triple: [Bong County, hasTown, Salala]
Generated description
Salala is a town in central Liberia that serves as an important local hub within Bong County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Salala
Target entity description: Salala is a town in central Liberia that serves as an important local hub within Bong County.
  • A. Salayea
    Salayea is a town in northwestern Liberia located within Lofa County.
  • B. Salora
    Salora was a prominent Finnish electronics manufacturer best known for producing televisions and radios, and it played a key role in the industrial history of Salo, Finland.
  • C. Lalsalu
    Lalsalu is a classic Bengali novel by Syed Waliullah that explores religious hypocrisy and rural life in East Bengal.
  • D. Kalsa
    Kalsa is a historic district of Palermo, Italy, known for its Arab-Norman heritage, medieval streets, and vibrant cultural life.
  • E. Lasbela
    Lasbela is a coastal district and city in Pakistan’s Balochistan province, known for its strategic location near Karachi and its mix of industrial, agricultural, and fishing activities.
  • 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_69ca8395c438819087d7cb844ab5990c completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc668e5c108190b08f9cd6b4fd4a8b completed April 1, 2026, 12:27 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfc1d965cc8190bad0a990df318698 completed April 3, 2026, 1:34 p.m.
NEDg Description generation batch_69cfc3b3044c81908631fee4ffe5c25f completed April 3, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_69cfc41fca3081908d8c2515c98283de completed April 3, 2026, 1:43 p.m.
Created at: March 30, 2026, 6:57 p.m.