Triple

T2840300
Position Surface form Disambiguated ID Type / Status
Subject Ernest Haller E62449 entity
Predicate familyName P18 FINISHED
Object Haller
Haller is a surname most notably associated with Ernest Haller, an American cinematographer renowned for his work in classic Hollywood films.
 E306154 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: Haller | Statement: [Ernest Haller, familyName, Haller]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Haller
Context triple: [Ernest Haller, familyName, Haller]
  • A. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • B. Haldenstein
    Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
  • C. Lindauer
    Lindauer is a German surname borne by various notable individuals across fields such as science, art, and public life.
  • D. Freyung
    Freyung is a small town in southeastern Bavaria, Germany, known as a gateway to the Bavarian Forest region.
  • E. Horst
    Horst is the taxpayer involved as the respondent in the landmark U.S. Supreme Court tax case Helvering v. Horst, which helped define the assignment-of-income doctrine.
  • 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: Haller
Triple: [Ernest Haller, familyName, Haller]
Generated description
Haller is a surname most notably associated with Ernest Haller, an American cinematographer renowned for his work in classic Hollywood films.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Haller
Target entity description: Haller is a surname most notably associated with Ernest Haller, an American cinematographer renowned for his work in classic Hollywood films.
  • A. Erasbach
    Erasbach is a small locality in Bavaria, Germany, best known as the birthplace of the composer Christoph Willibald Gluck.
  • B. Haldenstein
    Haldenstein is a small Swiss village in the canton of Graubünden, known in architecture circles as the longtime base of renowned architect Peter Zumthor.
  • C. Lindauer
    Lindauer is a German surname borne by various notable individuals across fields such as science, art, and public life.
  • D. Freyung
    Freyung is a small town in southeastern Bavaria, Germany, known as a gateway to the Bavarian Forest region.
  • E. Horst
    Horst is the taxpayer involved as the respondent in the landmark U.S. Supreme Court tax case Helvering v. Horst, which helped define the assignment-of-income doctrine.
  • 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_69ab4c3d16bc81908b3a1c98fbd287fe completed March 6, 2026, 9:50 p.m.
NER Named-entity recognition batch_69abdf15b7288190a03d1193cc0544a6 completed March 7, 2026, 8:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69b01d7705108190a986d3def0c08f7b completed March 10, 2026, 1:32 p.m.
NEDg Description generation batch_69b01fbe078c8190ba786122afb4f54b completed March 10, 2026, 1:42 p.m.
NED2 Entity disambiguation (via description) batch_69b020f0f6208190b134f3472b50fb1b completed March 10, 2026, 1:47 p.m.
Created at: March 6, 2026, 10:01 p.m.