Triple

T12107162
Position Surface form Disambiguated ID Type / Status
Subject Haya Harareet E288331 entity
Predicate familyName P18 FINISHED
Object Harareet
Harareet is the surname of Haya Harareet, an Israeli actress best known for her role as Esther in the 1959 film "Ben-Hur."
 E966839 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: Harareet | Statement: [Haya Harareet, familyName, Harareet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harareet
Context triple: [Haya Harareet, familyName, Harareet]
  • A. Buhera
    Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
  • B. Hakor
    Hakor was a pharaoh of ancient Egypt’s Twenty-ninth Dynasty, known for his efforts to maintain Egyptian independence against Persian domination.
  • C. Manzala
    Manzala is a town in northeastern Egypt situated near Lake Manzala and known for its fishing and agricultural activities.
  • D. Hadiyya
    Hadiyya is a Cushitic language spoken primarily by the Hadiya people in southern Ethiopia.
  • E. Hawiyah
    Hawiyah is a major gas plant and associated residential/industrial area in eastern Saudi Arabia that supports processing operations for the vast Ghawar oil field.
  • 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: Harareet
Triple: [Haya Harareet, familyName, Harareet]
Generated description
Harareet is the surname of Haya Harareet, an Israeli actress best known for her role as Esther in the 1959 film "Ben-Hur."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harareet
Target entity description: Harareet is the surname of Haya Harareet, an Israeli actress best known for her role as Esther in the 1959 film "Ben-Hur."
  • A. Buhera
    Buhera is a rural town and district center in eastern Zimbabwe known for its agricultural activities and location within Manicaland Province.
  • B. Hakor
    Hakor was a pharaoh of ancient Egypt’s Twenty-ninth Dynasty, known for his efforts to maintain Egyptian independence against Persian domination.
  • C. Manzala
    Manzala is a town in northeastern Egypt situated near Lake Manzala and known for its fishing and agricultural activities.
  • D. Hadiyya
    Hadiyya is a Cushitic language spoken primarily by the Hadiya people in southern Ethiopia.
  • E. Hawiyah
    Hawiyah is a major gas plant and associated residential/industrial area in eastern Saudi Arabia that supports processing operations for the vast Ghawar oil field.
  • 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d915632dc48190863e0239cef37e24 completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f6795bf88190891acf918a432bef completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f60263bc6c8190b867b4af20305e57 completed May 2, 2026, 1:55 p.m.
NED2 Entity disambiguation (via description) batch_69f6033935c08190980bd69395c250e4 completed May 2, 2026, 1:59 p.m.
Created at: April 8, 2026, 9:49 p.m.