Triple

T20322721
Position Surface form Disambiguated ID Type / Status
Subject Taiz Governorate E492246 entity
Predicate hasPort P35 FINISHED
Object Mocha
Mocha is a historic Yemeni port city on the Red Sea, once a major center of the global coffee trade.
E1423871 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: Mocha | Statement: [Taiz Governorate, hasPort, Mocha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mocha
Context triple: [Taiz Governorate, hasPort, Mocha]
  • A. Mocha
    Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
  • B. Mocha
    Mocha is a subsidiary peak of the Carihuairazo volcanic massif in the Ecuadorian Andes.
  • C. Caffe
    Caffe is an open-source deep learning framework known for its speed and modular design, widely used in computer vision research and applications.
  • D. Koffee
    Koffee is a Jamaican reggae and dancehall singer, songwriter, and rapper known for her Grammy-winning EP "Rapture" and hit single "Toast."
  • E. MOCCA
    MOCCA is a Toronto-based art institution dedicated to exhibiting and promoting contemporary Canadian art and artists.
  • 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: Mocha
Triple: [Taiz Governorate, hasPort, Mocha]
Generated description
Mocha is a historic Yemeni port city on the Red Sea, once a major center of the global coffee trade.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mocha
Target entity description: Mocha is a historic Yemeni port city on the Red Sea, once a major center of the global coffee trade.
  • A. Mocha
    Mocha is a popular JavaScript test framework used primarily for running unit and integration tests in Node.js and browser-based applications.
  • B. Mocha
    Mocha is a subsidiary peak of the Carihuairazo volcanic massif in the Ecuadorian Andes.
  • C. Caffe
    Caffe is an open-source deep learning framework known for its speed and modular design, widely used in computer vision research and applications.
  • D. Koffee
    Koffee is a Jamaican reggae and dancehall singer, songwriter, and rapper known for her Grammy-winning EP "Rapture" and hit single "Toast."
  • E. MOCCA
    MOCCA is a Toronto-based art institution dedicated to exhibiting and promoting contemporary Canadian art and artists.
  • 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_69e0b4a0134081909113563e1c3ba68a completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6778d95dc81909b1c87d26b5d3a33 completed April 20, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a08612ae0fc8190b71aed985088eb59 completed May 16, 2026, 12:20 p.m.
NEDg Description generation batch_6a0862c7eaa081909932483432f2fa9a completed May 16, 2026, 12:27 p.m.
NED2 Entity disambiguation (via description) batch_6a08634352288190976327bca8ea3986 completed May 16, 2026, 12:29 p.m.
Created at: April 16, 2026, 11:20 a.m.