Triple

T2587330
Position Surface form Disambiguated ID Type / Status
Subject Patricia E58034 entity
Predicate hasVariant P455 FINISHED
Object Tisha
Tisha is a feminine given name, often used as a diminutive or variant of names like Patricia or Letitia.
E278784 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: Tisha | Statement: [Patricia, hasVariant, Tisha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tisha
Context triple: [Patricia, hasVariant, Tisha]
  • A. Shira
    Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
  • B. Kirsha
    Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
  • C. Shosha
    Shosha is a novel by Nobel Prize–winning author Isaac Bashevis Singer that portrays a doomed love story set against the backdrop of pre–World War II Jewish Warsaw.
  • D. Shimsha
    Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
  • E. Ta-Shema
    Ta-Shema was the ancient Egyptian term for Upper Egypt, the southern region of the Nile Valley that formed one of the two core lands of the Egyptian kingdom.
  • 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: Tisha
Triple: [Patricia, hasVariant, Tisha]
Generated description
Tisha is a feminine given name, often used as a diminutive or variant of names like Patricia or Letitia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tisha
Target entity description: Tisha is a feminine given name, often used as a diminutive or variant of names like Patricia or Letitia.
  • A. Shira
    Shira is the eroded western volcanic cone and plateau of Mount Kilimanjaro, forming one of the mountain’s three main summits.
  • B. Kirsha
    Kirsha is a central character in Naguib Mahfouz’s novel "Midaq Alley," known as the café owner whose personal life and hidden desires reflect the social and moral tensions of mid-20th-century Cairo.
  • C. Shosha
    Shosha is a novel by Nobel Prize–winning author Isaac Bashevis Singer that portrays a doomed love story set against the backdrop of pre–World War II Jewish Warsaw.
  • D. Shimsha
    Shimsha is a river in southern India that flows through Karnataka and is known for its waterfalls and contribution to the Kaveri river system.
  • E. Ta-Shema
    Ta-Shema was the ancient Egyptian term for Upper Egypt, the southern region of the Nile Valley that formed one of the two core lands of the Egyptian kingdom.
  • 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_69ab4ac019c8819094add11c46706e32 completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abd3f8a3888190889c537e6df07305 completed March 7, 2026, 7:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69af65848e788190b2b01595540b1a10 completed March 10, 2026, 12:27 a.m.
NEDg Description generation batch_69af6694dd248190ad6d579d504b5f27 completed March 10, 2026, 12:32 a.m.
NED2 Entity disambiguation (via description) batch_69af677577c88190be9a66fea85ab899 completed March 10, 2026, 12:36 a.m.
Created at: March 6, 2026, 9:49 p.m.