Triple

T4005390
Position Surface form Disambiguated ID Type / Status
Subject Ayelet Zurer E89512 entity
Predicate spouse P13 FINISHED
Object Gilad Londovski
Gilad Londovski is an Israeli professional who is best known as the husband of acclaimed actress Ayelet Zurer.
E407482 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: Gilad Londovski | Statement: [Ayelet Zurer, spouse, Gilad Londovski]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gilad Londovski
Context triple: [Ayelet Zurer, spouse, Gilad Londovski]
  • A. Harel Weinstein
    Harel Weinstein is an Israeli-American neuroscientist and biophysicist known for his work on membrane proteins and computational neuroscience.
  • B. Mark Shtaif
    Mark Shtaif is an Israeli electrical engineer and academic who serves as rector of Tel Aviv University and is known for his research in optical communications and photonics.
  • C. Ilan Eshkeri
    Ilan Eshkeri is a British composer known for his orchestral film scores and collaborations on movies, television, and video games.
  • D. Michael Shvo
    Michael Shvo is a high-profile real estate developer and art collector known for leading luxury property projects in major global cities.
  • E. Joshua Ilan Gad
    Joshua Ilan Gad is an American actor and comedian best known for voicing Olaf in Disney's Frozen franchise and for his roles in film, television, and on Broadway.
  • 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: Gilad Londovski
Triple: [Ayelet Zurer, spouse, Gilad Londovski]
Generated description
Gilad Londovski is an Israeli professional who is best known as the husband of acclaimed actress Ayelet Zurer.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gilad Londovski
Target entity description: Gilad Londovski is an Israeli professional who is best known as the husband of acclaimed actress Ayelet Zurer.
  • A. Harel Weinstein
    Harel Weinstein is an Israeli-American neuroscientist and biophysicist known for his work on membrane proteins and computational neuroscience.
  • B. Mark Shtaif
    Mark Shtaif is an Israeli electrical engineer and academic who serves as rector of Tel Aviv University and is known for his research in optical communications and photonics.
  • C. Ilan Eshkeri
    Ilan Eshkeri is a British composer known for his orchestral film scores and collaborations on movies, television, and video games.
  • D. Michael Shvo
    Michael Shvo is a high-profile real estate developer and art collector known for leading luxury property projects in major global cities.
  • E. Joshua Ilan Gad
    Joshua Ilan Gad is an American actor and comedian best known for voicing Olaf in Disney's Frozen franchise and for his roles in film, television, and on Broadway.
  • 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_69aed9585e788190bec2d39deba3750f completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aefa5f7b308190adaad864eec98936 completed March 9, 2026, 4:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c648d3c8190a85e5cdfb20f6044 completed March 14, 2026, 11:54 a.m.
NEDg Description generation batch_69b54cf3da208190aa844c9ea66354fe completed March 14, 2026, 11:56 a.m.
NED2 Entity disambiguation (via description) batch_69b55159dc288190a63d5f5164b73bbb completed March 14, 2026, 12:15 p.m.
Created at: March 9, 2026, 3:34 p.m.