Triple

T1900866
Position Surface form Disambiguated ID Type / Status
Subject Sumer E37685 entity
Predicate hasCityState P25797 FINISHED
Object Kish
Kish was an important ancient Sumerian city-state in Mesopotamia, often associated with early kingship traditions and political power in the region.
E212532 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: Kish | Statement: [Sumer, hasCityState, Kish]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kish
Context triple: [Sumer, hasCityState, Kish]
  • A. Kish
    Kish is a Benjaminite figure in the Hebrew Bible best known as the father of Israel’s first king, Saul.
  • B. Aigai
    Aigai was the ancient capital of the kingdom of Macedon, historically significant as the royal seat and burial place of its kings before the rise of Pella.
  • C. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • D. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • E. Kyodai
    Kyodai is the common abbreviated name for Kyoto University, one of Japan’s most prestigious national research universities.
  • 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: Kish
Triple: [Sumer, hasCityState, Kish]
Generated description
Kish was an important ancient Sumerian city-state in Mesopotamia, often associated with early kingship traditions and political power in the region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kish
Target entity description: Kish was an important ancient Sumerian city-state in Mesopotamia, often associated with early kingship traditions and political power in the region.
  • A. Kish
    Kish is a Benjaminite figure in the Hebrew Bible best known as the father of Israel’s first king, Saul.
  • B. Aigai
    Aigai was the ancient capital of the kingdom of Macedon, historically significant as the royal seat and burial place of its kings before the rise of Pella.
  • C. Kanuma
    Kanuma is a regional harvest festival celebrated mainly in Andhra Pradesh and Telangana as part of the multi-day Makar Sankranti festivities, focusing on cattle worship and agricultural prosperity.
  • D. Kamen
    Kamen is a surname most prominently associated with American inventor and entrepreneur Dean Kamen, known for creating the Segway and numerous medical devices.
  • E. Kyodai
    Kyodai is the common abbreviated name for Kyoto University, one of Japan’s most prestigious national research universities.
  • 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_69a8861be7148190a680937ec451a304 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb7c376208190bbf28504f1aac881 completed March 7, 2026, 5:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69adeaf2c2908190bd050dee1576b36f completed March 8, 2026, 9:32 p.m.
NEDg Description generation batch_69adeb8b3d2c8190b13c03ce944f436a completed March 8, 2026, 9:35 p.m.
NED2 Entity disambiguation (via description) batch_69adec123cc481908e55dfbe4f4da095 completed March 8, 2026, 9:37 p.m.
Created at: March 4, 2026, 7:35 p.m.