Triple

T16785350
Position Surface form Disambiguated ID Type / Status
Subject Otto Harbach E407956 entity
Predicate familyName P18 FINISHED
Object Harbach
Harbach is a surname most notably associated with Otto Harbach, an American lyricist and librettist of early 20th-century musical theatre.
 E1267555 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: Harbach | Statement: [Otto Harbach, familyName, Harbach]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harbach
Context triple: [Otto Harbach, familyName, Harbach]
  • A. Schambach
    Schambach is a small river in Bavaria, Germany, that flows into the Altmühl as one of its tributaries.
  • B. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • C. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • D. Schwalmstadt
    Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
  • E. Nussloch
    Nussloch is a small town in southwestern Germany, known in part for hosting the headquarters of medical technology company Leica Biosystems.
  • 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: Harbach
Triple: [Otto Harbach, familyName, Harbach]
Generated description
Harbach is a surname most notably associated with Otto Harbach, an American lyricist and librettist of early 20th-century musical theatre.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harbach
Target entity description: Harbach is a surname most notably associated with Otto Harbach, an American lyricist and librettist of early 20th-century musical theatre.
  • A. Schambach
    Schambach is a small river in Bavaria, Germany, that flows into the Altmühl as one of its tributaries.
  • B. Fritzlar
    Fritzlar is a historic town in northern Hesse, Germany, known for its well-preserved medieval old town and its significance in early German Christian history.
  • C. Gevelsberg
    Gevelsberg is a town in North Rhine-Westphalia, Germany, situated in the Ennepe-Ruhr district within the Ruhr metropolitan region.
  • D. Schwalmstadt
    Schwalmstadt is a small town in the Schwalm-Eder district of northern Hesse, Germany, known for its historic half-timbered architecture and picturesque setting in the Schwalm River valley.
  • E. Nussloch
    Nussloch is a small town in southwestern Germany, known in part for hosting the headquarters of medical technology company Leica Biosystems.
  • 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_69d8839270588190886720d9519bbf8f completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3b21996cc81909deb88545af7079f completed April 18, 2026, 4:32 p.m.
NED1 Entity disambiguation (via context triple) batch_6a01a7e006808190a1b2838a32662ce0 completed May 11, 2026, 9:56 a.m.
NEDg Description generation batch_6a01a912497c8190a8e09e5aaaac591a completed May 11, 2026, 10:01 a.m.
NED2 Entity disambiguation (via description) batch_6a01a96980ac81908a40b1e36c31b796 completed May 11, 2026, 10:03 a.m.
Created at: April 10, 2026, 5:22 a.m.