Triple

T7235418
Position Surface form Disambiguated ID Type / Status
Subject Harold F. Kress E155211 entity
Predicate familyName P18 FINISHED
Object Kress
Kress is a surname most notably associated with Harold F. Kress, an Academy Award–winning American film editor.
 E651004 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: Kress | Statement: [Harold F. Kress, familyName, Kress]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kress
Context triple: [Harold F. Kress, familyName, Kress]
  • A. Schiffrin
    Schiffrin is a surname most notably associated with André Schiffrin, an influential publisher and intellectual known for his work in progressive and independent publishing.
  • B. Meyer-Lübke
    Meyer-Lübke is the surname of Wilhelm Meyer-Lübke, a prominent Swiss linguist known for his influential work in Romance philology.
  • C. Tiskre
    Tiskre is a residential settlement in northern Estonia, situated near the capital Tallinn and known for its coastal location and suburban character.
  • D. Kiesler
    Kiesler is the birth surname of Austrian-born Hollywood actress and inventor Hedy Lamarr.
  • E. Keutenberg
    Keutenberg is a famously steep and decisive hill in the Dutch Limburg region, often shaping the outcome of professional cycling races.
  • 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: Kress
Triple: [Harold F. Kress, familyName, Kress]
Generated description
Kress is a surname most notably associated with Harold F. Kress, an Academy Award–winning American film editor.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kress
Target entity description: Kress is a surname most notably associated with Harold F. Kress, an Academy Award–winning American film editor.
  • A. Schiffrin
    Schiffrin is a surname most notably associated with André Schiffrin, an influential publisher and intellectual known for his work in progressive and independent publishing.
  • B. Meyer-Lübke
    Meyer-Lübke is the surname of Wilhelm Meyer-Lübke, a prominent Swiss linguist known for his influential work in Romance philology.
  • C. Tiskre
    Tiskre is a residential settlement in northern Estonia, situated near the capital Tallinn and known for its coastal location and suburban character.
  • D. Kiesler
    Kiesler is the birth surname of Austrian-born Hollywood actress and inventor Hedy Lamarr.
  • E. Keutenberg
    Keutenberg is a famously steep and decisive hill in the Dutch Limburg region, often shaping the outcome of professional cycling races.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea33dd3481908ebb050e1fab5aaa completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc32d6c48190ae78b3d1227bb868 completed March 28, 2026, 12:40 p.m.
NEDg Description generation batch_69c7cdce27548190bb0c026f70fd915a completed March 28, 2026, 12:47 p.m.
NED2 Entity disambiguation (via description) batch_69c7ce41ed088190b423ed7955c68eeb completed March 28, 2026, 12:49 p.m.
Created at: March 27, 2026, 2:55 p.m.