Triple

T16773779
Position Surface form Disambiguated ID Type / Status
Subject Tripylon E407670 entity
Predicate connects P390 FINISHED
Object Hadish
Hadish was one of the main palace complexes within the ancient Achaemenid capital of Persepolis, likely serving as a royal residence.
E1234002 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: Hadish | Statement: [Tripylon, connects, Hadish]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hadish
Context triple: [Tripylon, connects, Hadish]
  • A. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • B. Hadiyya Afoo
    Hadiyya Afoo is a Cushitic language spoken primarily by the Hadiyya people in southern Ethiopia.
  • C. Hanan
    Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
  • D. Buraydah
    Buraydah is a major city in central Saudi Arabia and the capital of Al-Qassim Region, known as an important agricultural and commercial center.
  • E. Fahdah
    Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
  • 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: Hadish
Triple: [Tripylon, connects, Hadish]
Generated description
Hadish was one of the main palace complexes within the ancient Achaemenid capital of Persepolis, likely serving as a royal residence.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hadish
Target entity description: Hadish was one of the main palace complexes within the ancient Achaemenid capital of Persepolis, likely serving as a royal residence.
  • A. Hamida
    Hamida is a central, ambitious young woman in Naguib Mahfouz’s novel "Midaq Alley," whose desire to escape poverty and traditional constraints drives much of the story’s conflict.
  • B. Hadiyya Afoo
    Hadiyya Afoo is a Cushitic language spoken primarily by the Hadiyya people in southern Ethiopia.
  • C. Hanan
    Hanan is a given name most notably borne by Palestinian legislator, activist, and scholar Hanan Ashrawi.
  • D. Buraydah
    Buraydah is a major city in central Saudi Arabia and the capital of Al-Qassim Region, known as an important agricultural and commercial center.
  • E. Fahdah
    Fahdah is a Saudi princess, formally known as Princess Fahdah Mohammed Abunayyan, associated with the Saudi royal family.
  • 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b037c5708190ba604e7707b5a8a2 completed April 18, 2026, 4:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00aafc28c0819084ecd6e5be6adec9 completed May 10, 2026, 3:57 p.m.
NEDg Description generation batch_6a00abfe035881909330d356bb497229 completed May 10, 2026, 4:02 p.m.
NED2 Entity disambiguation (via description) batch_6a00ac54a11c81909afe9244e9fe0656 completed May 10, 2026, 4:03 p.m.
Created at: April 10, 2026, 5:21 a.m.