Triple

T17182304
Position Surface form Disambiguated ID Type / Status
Subject Eisenring E417013 entity
Predicate hasAlly P600 FINISHED
Object Schmitz
Schmitz is a character who serves as an ally and accomplice to Eisenring in Friedrich Dürrenmatt’s play "The Visit."
E1255754 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: Schmitz | Statement: [Eisenring, hasAlly, Schmitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Schmitz
Context triple: [Eisenring, hasAlly, Schmitz]
  • A. Schmitz
    Schmitz is one of the two manipulative arsonists who infiltrate the bourgeois household in Max Frisch’s play "Biedermann und die Brandstifter."
  • B. Wülpke
    Wülpke is a former municipality in North Rhine-Westphalia, Germany, that now forms part of the town of Porta Westfalica.
  • C. Stottlemeyer
    Stottlemeyer is the surname of Captain Leland Stottlemeyer, a central police character from the television series "Monk."
  • D. Suter
    Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
  • E. Menzlin
    Menzlin is a small locality in northeastern Germany, historically part of Pomerania.
  • 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: Schmitz
Triple: [Eisenring, hasAlly, Schmitz]
Generated description
Schmitz is a character who serves as an ally and accomplice to Eisenring in Friedrich Dürrenmatt’s play "The Visit."
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Schmitz
Target entity description: Schmitz is a character who serves as an ally and accomplice to Eisenring in Friedrich Dürrenmatt’s play "The Visit."
  • A. Schmitz
    Schmitz is one of the two manipulative arsonists who infiltrate the bourgeois household in Max Frisch’s play "Biedermann und die Brandstifter."
  • B. Wülpke
    Wülpke is a former municipality in North Rhine-Westphalia, Germany, that now forms part of the town of Porta Westfalica.
  • C. Stottlemeyer
    Stottlemeyer is the surname of Captain Leland Stottlemeyer, a central police character from the television series "Monk."
  • D. Suter
    Suter is a surname of Germanic origin, often associated with individuals of Swiss or German heritage.
  • E. Menzlin
    Menzlin is a small locality in northeastern Germany, historically part of Pomerania.
  • 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_69d886d5f34c8190b24564dfaa63f3fb completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e42d934ec08190acc47073758ac3c0 completed April 19, 2026, 1:19 a.m.
NED1 Entity disambiguation (via context triple) batch_6a015fca04cc8190a9df230078fbe268 completed May 11, 2026, 4:49 a.m.
NEDg Description generation batch_6a0161e5f6f0819083c57feac088f531 completed May 11, 2026, 4:58 a.m.
NED2 Entity disambiguation (via description) batch_6a0162785e7081908d57801eeae7cf67 completed May 11, 2026, 5 a.m.
Created at: April 10, 2026, 5:37 a.m.