Triple

T16300059
Position Surface form Disambiguated ID Type / Status
Subject Avrom Sutzkever E395759 entity
Predicate notableWork P4 FINISHED
Object Fun Vilner geto
Fun Vilner geto is a Yiddish poetry collection by Avrom Sutzkever that powerfully chronicles life and resistance in the Vilna Ghetto during the Holocaust.
 E1206188 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: Fun Vilner geto | Statement: [Avrom Sutzkever, notableWork, Fun Vilner geto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Fun Vilner geto
Context triple: [Avrom Sutzkever, notableWork, Fun Vilner geto]
  • A. Geto
    Geto is a dialect of the Sebat Bet Gurage language spoken by the Gurage people in Ethiopia.
  • B. Funka
    Funka is a small village in northern Poland known for its scenic lakeside setting and recreational access to Lake Charzykowskie.
  • C. Reppisch
    Reppisch is a river in the canton of Zurich, Switzerland, that flows through the Reppischtal valley before joining the Limmat.
  • D. Popular Music from Vittula
    Popular Music from Vittula is a darkly comic coming-of-age novel set in a remote northern Swedish town, exploring friendship, identity, and the transformative power of rock music.
  • E. Ershevka
    Ershevka is a rural locality in Kaluga Oblast, Russia.
  • 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: Fun Vilner geto
Triple: [Avrom Sutzkever, notableWork, Fun Vilner geto]
Generated description
Fun Vilner geto is a Yiddish poetry collection by Avrom Sutzkever that powerfully chronicles life and resistance in the Vilna Ghetto during the Holocaust.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Fun Vilner geto
Target entity description: Fun Vilner geto is a Yiddish poetry collection by Avrom Sutzkever that powerfully chronicles life and resistance in the Vilna Ghetto during the Holocaust.
  • A. Geto
    Geto is a dialect of the Sebat Bet Gurage language spoken by the Gurage people in Ethiopia.
  • B. Funka
    Funka is a small village in northern Poland known for its scenic lakeside setting and recreational access to Lake Charzykowskie.
  • C. Reppisch
    Reppisch is a river in the canton of Zurich, Switzerland, that flows through the Reppischtal valley before joining the Limmat.
  • D. Popular Music from Vittula
    Popular Music from Vittula is a darkly comic coming-of-age novel set in a remote northern Swedish town, exploring friendship, identity, and the transformative power of rock music.
  • E. Ershevka
    Ershevka is a rural locality in Kaluga Oblast, Russia.
  • 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_69d87f23bb088190a16fbb91a1957ea5 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e25e31c9e8819094593f3aeb44f2ca completed April 17, 2026, 4:22 p.m.
NED1 Entity disambiguation (via context triple) batch_6a001f9d7ef48190b7acebebcb9608c3 completed May 10, 2026, 6:03 a.m.
NEDg Description generation batch_6a0021459c4081908e4c1d2e0bc8a5be completed May 10, 2026, 6:10 a.m.
NED2 Entity disambiguation (via description) batch_6a002221fe7c819083c8ede5e63b0908 completed May 10, 2026, 6:13 a.m.
Created at: April 10, 2026, 5:06 a.m.