Triple

T1868306
Position Surface form Disambiguated ID Type / Status
Subject Río Muni E34972 entity
Predicate containsProvince P11085 FINISHED
Object Djibloho
Djibloho is a planned administrative capital city and province of Equatorial Guinea located in the mainland region of Río Muni.
E207849 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: Djibloho | Statement: [Río Muni, containsProvince, Djibloho]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Djibloho
Context triple: [Río Muni, containsProvince, Djibloho]
  • A. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • B. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • C. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • D. Garki
    Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
  • E. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma 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: Djibloho
Triple: [Río Muni, containsProvince, Djibloho]
Generated description
Djibloho is a planned administrative capital city and province of Equatorial Guinea located in the mainland region of Río Muni.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Djibloho
Target entity description: Djibloho is a planned administrative capital city and province of Equatorial Guinea located in the mainland region of Río Muni.
  • A. Anseba
    Anseba is a central region of Eritrea known for its diverse ethnic communities, agriculture, and the regional capital Keren.
  • B. Negombo
    Negombo is a coastal city in western Sri Lanka known historically as a strategic colonial port and today for its fishing industry and beach tourism.
  • C. Kumba
    Kumba is a renowned steel roller coaster at Busch Gardens Tampa Bay, famous for its intense inversions and smooth, high-speed layout.
  • D. Garki
    Garki is a prominent administrative and commercial district in Nigeria’s capital city, Abuja, housing numerous government offices, businesses, and residential areas.
  • E. Kibondo
    Kibondo is a town in western Tanzania that serves as an administrative and commercial center in the Kigoma Region.
  • 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_69a88600b2f88190bc09303e68ab517e completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69abb0b6ac108190921c197abc5ab5b5 completed March 7, 2026, 4:59 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1d8dd8881909189029a047bc2b4 completed March 8, 2026, 7:45 p.m.
NEDg Description generation batch_69add28b804c8190a625e5d1405c59be completed March 8, 2026, 7:48 p.m.
NED2 Entity disambiguation (via description) batch_69add35731588190a13c969490ca2c09 completed March 8, 2026, 7:51 p.m.
Created at: March 4, 2026, 7:34 p.m.