Triple

T19071902
Position Surface form Disambiguated ID Type / Status
Subject southern Jerusalem E466812 entity
Predicate hasNeighborhood P40 FINISHED
Object Katamon
Katamon is a historic residential neighborhood in Jerusalem known for its mix of old stone buildings, diverse population, and proximity to major cultural and religious sites.
 E1357383 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: Katamon | Statement: [southern Jerusalem, hasNeighborhood, Katamon]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Katamon
Context triple: [southern Jerusalem, hasNeighborhood, Katamon]
  • A. Manono
    Manono is a small inhabited island in Samoa, situated in the strait between the larger islands of Upolu and Savai'i.
  • B. Koromo
    Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Akaiami
    Akaiami is a small, picturesque islet in the Aitutaki Lagoon of the Cook Islands, known for its white-sand beaches and clear turquoise waters.
  • E. Tanno
    Tanno is a district or locality within the city of Kitami in Hokkaido, Japan.
  • 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: Katamon
Triple: [southern Jerusalem, hasNeighborhood, Katamon]
Generated description
Katamon is a historic residential neighborhood in Jerusalem known for its mix of old stone buildings, diverse population, and proximity to major cultural and religious sites.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Katamon
Target entity description: Katamon is a historic residential neighborhood in Jerusalem known for its mix of old stone buildings, diverse population, and proximity to major cultural and religious sites.
  • A. Manono
    Manono is a small inhabited island in Samoa, situated in the strait between the larger islands of Upolu and Savai'i.
  • B. Koromo
    Koromo was the former name of what is now Toyota City in Aichi Prefecture, Japan, historically known as a regional center before becoming synonymous with the Toyota automobile company.
  • C. Moruya
    Moruya is a coastal town in New South Wales, Australia, known for its scenic river setting, nearby beaches, and historic granite quarries.
  • D. Akaiami
    Akaiami is a small, picturesque islet in the Aitutaki Lagoon of the Cook Islands, known for its white-sand beaches and clear turquoise waters.
  • E. Tanno
    Tanno is a district or locality within the city of Kitami in Hokkaido, Japan.
  • 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_69d8dd04f4488190b1121cc53ef2bfd6 completed April 10, 2026, 11:20 a.m.
NER Named-entity recognition batch_69e5e19fa6948190bdf8e8ec022e12f2 completed April 20, 2026, 8:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a05d35ca6848190a6d6695f9156488d completed May 14, 2026, 1:51 p.m.
NEDg Description generation batch_6a05d53fbdf481908f60131dd2fcb15d completed May 14, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_6a05d5a12d708190922eb39ce2b515f8 completed May 14, 2026, 2:01 p.m.
Created at: April 10, 2026, 12:04 p.m.