Triple

T12693417
Position Surface form Disambiguated ID Type / Status
Subject Jeremy King E303266 entity
Predicate coFounded P104 FINISHED
Object Manzi’s
Manzi’s is a London seafood restaurant known for its classic brasserie style and was co-founded by renowned restaurateur Jeremy King.
E998196 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: Manzi’s | Statement: [Jeremy King, coFounded, Manzi’s]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manzi’s
Context triple: [Jeremy King, coFounded, Manzi’s]
  • A. Gambiri Kati
    Gambiri Kati is an alternative name for the Tregami language, an Indo-Iranian language spoken in parts of eastern Afghanistan.
  • B. Musanze
    Musanze is a major town in northern Rwanda that serves as the primary gateway for tourists visiting Volcanoes National Park and its mountain gorillas.
  • C. Mansaka
    Mansaka is an Austronesian language spoken by the indigenous Mansaka people of southeastern Mindanao in the Philippines.
  • D. Ngbaka Minagende
    Ngbaka Minagende is a dialect of the Ngbaka language spoken by Ngbaka communities in Central Africa.
  • E. Muna
    Muna is an island in Indonesia known for its location in Southeast Sulawesi and its distinctive local culture and limestone landscapes.
  • 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: Manzi’s
Triple: [Jeremy King, coFounded, Manzi’s]
Generated description
Manzi’s is a London seafood restaurant known for its classic brasserie style and was co-founded by renowned restaurateur Jeremy King.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Manzi’s
Target entity description: Manzi’s is a London seafood restaurant known for its classic brasserie style and was co-founded by renowned restaurateur Jeremy King.
  • A. Gambiri Kati
    Gambiri Kati is an alternative name for the Tregami language, an Indo-Iranian language spoken in parts of eastern Afghanistan.
  • B. Musanze
    Musanze is a major town in northern Rwanda that serves as the primary gateway for tourists visiting Volcanoes National Park and its mountain gorillas.
  • C. Mansaka
    Mansaka is an Austronesian language spoken by the indigenous Mansaka people of southeastern Mindanao in the Philippines.
  • D. Ngbaka Minagende
    Ngbaka Minagende is a dialect of the Ngbaka language spoken by Ngbaka communities in Central Africa.
  • E. Muna
    Muna is a town in Mexico’s Yucatán state known as a gateway to the Puuc archaeological region and nearby Maya sites such as Uxmal.
  • 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_69d7bdef90d48190b46b88270e780946 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d961dbc91c8190bec50797bbd593db completed April 10, 2026, 8:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f671ae935c8190a7fc2cf3c0987248 completed May 2, 2026, 9:50 p.m.
NEDg Description generation batch_69f6740129688190b286ce7acb4848c7 completed May 2, 2026, 10 p.m.
NED2 Entity disambiguation (via description) batch_69f675249d248190933421df49d3a2ab completed May 2, 2026, 10:05 p.m.
Created at: April 9, 2026, 5:22 p.m.