Triple

T37137890
Position Surface form Disambiguated ID Type / Status
Subject Hatufim E920020 entity
Predicate hasCharacter P2308 FINISHED
Object Nurit Zach
Nurit Zach is a central character in the Israeli television drama "Hatufim" ("Prisoners of War"), which explores the emotional and familial impact of soldiers returning home after years in captivity.
E2238472 NE FINISHED

How this triple was built (2 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: Nurit Zach | Statement: [Hatufim, hasCharacter, Nurit Zach]
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: Nurit Zach
Triple: [Hatufim, hasCharacter, Nurit Zach]
Generated description
Nurit Zach is a central character in the Israeli television drama "Hatufim" ("Prisoners of War"), which explores the emotional and familial impact of soldiers returning home after years in captivity.

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_69f76e9e9d008190a250b0387c992c74 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fb3062e2a881908797d857bbeb4e86 completed May 6, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40cd9f2cd88190a092060977c8936d completed June 28, 2026, 7:30 a.m.
NEDg Description generation batch_6a40ce3d01a08190952db5afe4d11324 completed June 28, 2026, 7:33 a.m.
NED2 Entity disambiguation (via description) batch_6a40cec32e4c819095b877087cd7fcdd completed June 28, 2026, 7:35 a.m.
Created at: May 3, 2026, 4:15 p.m.