Triple

T4289487
Position Surface form Disambiguated ID Type / Status
Subject Gash-Barka E97352 entity
Predicate hasSettlement P1068 FINISHED
Object Haykota
Haykota is a town in Eritrea’s Gash-Barka region, known primarily as a local agricultural and administrative center.
 E429519 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: Haykota | Statement: [Gash-Barka, hasSettlement, Haykota]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haykota
Context triple: [Gash-Barka, hasSettlement, Haykota]
  • A. Hakitia
    Hakitia is a Judeo-Spanish dialect historically spoken by North African Sephardic Jews, blending Old Spanish with Hebrew and elements of Arabic.
  • B. Hayange
    Hayange is an industrial town in northeastern France known historically for its steel and ironworks in the Moselle department of the Grand Est region.
  • C. Harauti
    Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
  • D. Haymana
    Haymana is a rural district and town in central Turkey known for its thermal springs and agricultural landscape within Ankara Province.
  • E. Haise
    Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
  • 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: Haykota
Triple: [Gash-Barka, hasSettlement, Haykota]
Generated description
Haykota is a town in Eritrea’s Gash-Barka region, known primarily as a local agricultural and administrative center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haykota
Target entity description: Haykota is a town in Eritrea’s Gash-Barka region, known primarily as a local agricultural and administrative center.
  • A. Hakitia
    Hakitia is a Judeo-Spanish dialect historically spoken by North African Sephardic Jews, blending Old Spanish with Hebrew and elements of Arabic.
  • B. Hayange
    Hayange is an industrial town in northeastern France known historically for its steel and ironworks in the Moselle department of the Grand Est region.
  • C. Harauti
    Harauti is an Indo-Aryan dialect of the Rajasthani language spoken primarily in the Hadoti region of Rajasthan, India.
  • D. Haymana
    Haymana is a rural district and town in central Turkey known for its thermal springs and agricultural landscape within Ankara Province.
  • E. Haise
    Haise is the surname of Fred Haise, the American astronaut and Apollo 13 lunar module pilot.
  • 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_69b3454595848190a0e6bbb6a2bea040 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35061f5448190b3356b29a9129160 completed March 12, 2026, 11:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7307e3481909dfb55018f359589 completed March 14, 2026, 8:38 p.m.
NEDg Description generation batch_69b5c89e8cf88190b0f783c28dc2abdb completed March 14, 2026, 8:44 p.m.
NED2 Entity disambiguation (via description) batch_69b5c8f368908190a660b113ceefb7fb completed March 14, 2026, 8:45 p.m.
Created at: March 12, 2026, 11:08 p.m.