Triple

T15529728
Position Surface form Disambiguated ID Type / Status
Subject Hammond Beeby and Babka E370179 entity
Predicate hasNamePart P5298 FINISHED
Object Babka
Babka is an architectural firm that was part of the Chicago-based partnership Hammond Beeby and Babka, known for its work on prominent civic and institutional buildings.
 E1162535 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: Babka | Statement: [Hammond Beeby and Babka, hasNamePart, Babka]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Babka
Context triple: [Hammond Beeby and Babka, hasNamePart, Babka]
  • A. Babička
    Babička is a classic 1855 Czech novel by Božena Němcová that nostalgically portrays rural life and the wisdom of a beloved grandmother figure.
  • B. Babica
    Babica is a mountain peak located in the Maków Beskids range in southern Poland.
  • C. Babusch
    Babusch is a character in Bertolt Brecht’s play "Drums in the Night," appearing within its post–World War I German setting.
  • D. Lokma
    Lokma is a traditional Turkish dessert consisting of small deep-fried dough balls soaked in syrup, often served at celebrations and communal events.
  • E. Borek
    Borek is a traditional savory pastry made of thin layers of dough filled with ingredients like cheese, spinach, or meat, widely enjoyed across Turkey and the Balkans.
  • 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: Babka
Triple: [Hammond Beeby and Babka, hasNamePart, Babka]
Generated description
Babka is an architectural firm that was part of the Chicago-based partnership Hammond Beeby and Babka, known for its work on prominent civic and institutional buildings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Babka
Target entity description: Babka is an architectural firm that was part of the Chicago-based partnership Hammond Beeby and Babka, known for its work on prominent civic and institutional buildings.
  • A. Babička
    Babička is a classic 1855 Czech novel by Božena Němcová that nostalgically portrays rural life and the wisdom of a beloved grandmother figure.
  • B. Babica
    Babica is a mountain peak located in the Maków Beskids range in southern Poland.
  • C. Babusch
    Babusch is a character in Bertolt Brecht’s play "Drums in the Night," appearing within its post–World War I German setting.
  • D. Lokma
    Lokma is a traditional Turkish dessert consisting of small deep-fried dough balls soaked in syrup, often served at celebrations and communal events.
  • E. Borek
    Borek is a traditional savory pastry made of thin layers of dough filled with ingredients like cheese, spinach, or meat, widely enjoyed across Turkey and the Balkans.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0414773548190b3311515f9d957dd completed April 16, 2026, 1:54 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff3d5b989c8190a76612df167ba1dd completed May 9, 2026, 1:57 p.m.
NEDg Description generation batch_69ff3ea7d5ac81908bd1ee64de39dba7 completed May 9, 2026, 2:03 p.m.
NED2 Entity disambiguation (via description) batch_69ff413a68488190a6c8907e36a602dc completed May 9, 2026, 2:14 p.m.
Created at: April 10, 2026, 4:05 a.m.