Triple

T14510711
Position Surface form Disambiguated ID Type / Status
Subject Sifan Hassan E340387 entity
Predicate placeOfBirth P1 FINISHED
Object Adama E762155 NE FINISHED

How this triple was built (2 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: Adama | Statement: [Sifan Hassan, placeOfBirth, Adama]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Adama
Context triple: [Sifan Hassan, placeOfBirth, Adama]
  • A. Adama chosen
    Adama is a major Ethiopian city in the Oromia Region, known as an important commercial and transportation hub southeast of Addis Ababa.
  • B. Xala
    Xala is a 1974 satirical film (and earlier novel) by Ousmane Sembène that critiques post-independence African elites through the story of a corrupt businessman afflicted with impotence.
  • C. Adibou
    Adibou is a popular French educational video game series for young children that combines playful activities with early learning in subjects like reading, math, and science.
  • D. Djiba
    Djiba is a locality in the Ituri region of the Democratic Republic of the Congo, known as the birthplace of militia leader Thomas Lubanga Dyilo.
  • E. Ambouli
    Ambouli is a district of Djibouti City that hosts the country’s main international airport and related urban infrastructure.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e5b7b48190878be271840c265b completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da48b2c8190a906965a7ebcb607 completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.