Triple

T15744009
Position Surface form Disambiguated ID Type / Status
Subject Associated Dry Goods E381671 entity
Predicate owned P347 FINISHED
Object Pizitz
Pizitz was a prominent regional department store chain based in Birmingham, Alabama, known for its role as a major Southern retailer in the 20th century.
E1174259 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: Pizitz | Statement: [Associated Dry Goods, owned, Pizitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pizitz
Context triple: [Associated Dry Goods, owned, Pizitz]
  • A. Pitasch
    Pitasch was a former municipality in the canton of Graubünden in Switzerland, located in the Surselva region.
  • B. Pettnasco
    Pettnasco is a small Italian town situated on the shores of Lake Orta in the Piedmont region.
  • C. Moco
    Moco is the nickname of Brazilian Formula One driver José Carlos Pace, remembered for his Grand Prix victory and the Interlagos circuit later being named in his honor.
  • D. Pecile
    Pecile is a large colonnaded garden and pool complex within Hadrian’s Villa at Tivoli, designed as a central courtyard for leisure, reflection, and display of imperial grandeur.
  • E. Pister
    Pister is a German surname most notably borne by Hermann Pister, a Nazi SS officer and commandant of the Buchenwald concentration camp.
  • 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: Pizitz
Triple: [Associated Dry Goods, owned, Pizitz]
Generated description
Pizitz was a prominent regional department store chain based in Birmingham, Alabama, known for its role as a major Southern retailer in the 20th century.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pizitz
Target entity description: Pizitz was a prominent regional department store chain based in Birmingham, Alabama, known for its role as a major Southern retailer in the 20th century.
  • A. Pitasch
    Pitasch was a former municipality in the canton of Graubünden in Switzerland, located in the Surselva region.
  • B. Pettnasco
    Pettnasco is a small Italian town situated on the shores of Lake Orta in the Piedmont region.
  • C. Moco
    Moco is the nickname of Brazilian Formula One driver José Carlos Pace, remembered for his Grand Prix victory and the Interlagos circuit later being named in his honor.
  • D. Pecile
    Pecile is a large colonnaded garden and pool complex within Hadrian’s Villa at Tivoli, designed as a central courtyard for leisure, reflection, and display of imperial grandeur.
  • E. Pister
    Pister is a German surname most notably borne by Hermann Pister, a Nazi SS officer and commandant of the Buchenwald concentration camp.
  • 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_69d86d9e6b44819085d1f6a969ecb74c completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e0502c0c3c8190b8e512df307039c1 completed April 16, 2026, 2:57 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff8307824881909ba85e4c3da65d28 completed May 9, 2026, 6:55 p.m.
NEDg Description generation batch_69ff83ca33d08190816130bf2ea735df completed May 9, 2026, 6:58 p.m.
NED2 Entity disambiguation (via description) batch_69ff846436e48190b711da134c9a3b81 completed May 9, 2026, 7 p.m.
Created at: April 10, 2026, 4:46 a.m.