Triple

T9953365
Position Surface form Disambiguated ID Type / Status
Subject Lekki E195384 entity
Predicate associatedWith P37 FINISHED
Object Nokki
Nokki is likely a lesser-known entity, possibly a business, brand, or local initiative connected to the Lekki area of Lagos, Nigeria.
E830257 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: Nokki | Statement: [Lekki, associatedWith, Nokki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nokki
Context triple: [Lekki, associatedWith, Nokki]
  • A. Nokki
    Nokki is one of the four snow owl mascots created to represent the 1998 Winter Olympics held in Nagano, Japan.
  • B. Noki
    Noki are a species of shell-wearing, sea snail-like inhabitants of Isle Delfino known for their peaceful, oceanic lifestyle in the Super Mario series.
  • C. Nokia 3410
    The Nokia 3410 is an early-2000s GSM mobile phone known for its durable design, long battery life, and support for Java-based games and applications.
  • D. Mio
    Mio is the Japanese-led Mercury Magnetospheric Orbiter, a component of the joint ESA–JAXA BepiColombo mission designed to study Mercury’s magnetic field and space environment.
  • E. Nokia 3360
    The Nokia 3360 is a popular early-2000s candybar-style mobile phone known for its durability, long battery life, and classic features like SMS texting and built-in games such as Snake.
  • 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: Nokki
Triple: [Lekki, associatedWith, Nokki]
Generated description
Nokki is likely a lesser-known entity, possibly a business, brand, or local initiative connected to the Lekki area of Lagos, Nigeria.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Nokki
Target entity description: Nokki is likely a lesser-known entity, possibly a business, brand, or local initiative connected to the Lekki area of Lagos, Nigeria.
  • A. Nokki
    Nokki is one of the four snow owl mascots created to represent the 1998 Winter Olympics held in Nagano, Japan.
  • B. Noki
    Noki are a species of shell-wearing, sea snail-like inhabitants of Isle Delfino known for their peaceful, oceanic lifestyle in the Super Mario series.
  • C. Nokia 3410
    The Nokia 3410 is an early-2000s GSM mobile phone known for its durable design, long battery life, and support for Java-based games and applications.
  • D. Mio
    Mio is the Japanese-led Mercury Magnetospheric Orbiter, a component of the joint ESA–JAXA BepiColombo mission designed to study Mercury’s magnetic field and space environment.
  • E. Nokia 3360
    The Nokia 3360 is a popular early-2000s candybar-style mobile phone known for its durability, long battery life, and classic features like SMS texting and built-in games such as Snake.
  • 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_69ca82eaaa008190a54fa1a9f954b9ad completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb693918081908e9f96ef302235ad completed April 2, 2026, 12:21 a.m.
NED1 Entity disambiguation (via context triple) batch_69d2293dc93881908aff4cb3640c0edf completed April 5, 2026, 9:19 a.m.
NEDg Description generation batch_69d229b3b200819083aa90f64eaec9e8 completed April 5, 2026, 9:21 a.m.
NED2 Entity disambiguation (via description) batch_69d22a2d14fc8190b2493ce571811d43 completed April 5, 2026, 9:23 a.m.
Created at: March 30, 2026, 8:46 p.m.