Triple

T13779671
Position Surface form Disambiguated ID Type / Status
Subject Warehouse 13 E331100 entity
Predicate mainCharacter P1183 FINISHED
Object Leena
Leena is a key supporting character in the science fiction television series "Warehouse 13," known for running the bed-and-breakfast where the agents live and for her empathic connection to artifacts.
 E1060825 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: Leena | Statement: [Warehouse 13, mainCharacter, Leena]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Leena
Context triple: [Warehouse 13, mainCharacter, Leena]
  • A. Meena
    Meena is a shy teenage elephant with a powerful singing voice in the animated film "Sing."
  • B. Leela
    Leela is the one-eyed, tough yet compassionate spaceship captain from the animated television series "Futurama."
  • C. Leela
    Leela is a companion of the Fourth Doctor in the classic British science fiction television series Doctor Who.
  • D. Neeta
    Neeta is the tragic, self-sacrificing young woman at the center of Ritwik Ghatak’s classic Bengali film "Meghe Dhaka Tara."
  • E. Lasya
    Lasya is a graceful, expressive classical Indian dance style traditionally associated with feminine beauty and gentle, fluid movements.
  • 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: Leena
Triple: [Warehouse 13, mainCharacter, Leena]
Generated description
Leena is a key supporting character in the science fiction television series "Warehouse 13," known for running the bed-and-breakfast where the agents live and for her empathic connection to artifacts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Leena
Target entity description: Leena is a key supporting character in the science fiction television series "Warehouse 13," known for running the bed-and-breakfast where the agents live and for her empathic connection to artifacts.
  • A. Meena
    Meena is a shy teenage elephant with a powerful singing voice in the animated film "Sing."
  • B. Leela
    Leela is the one-eyed, tough yet compassionate spaceship captain from the animated television series "Futurama."
  • C. Leela
    Leela is a companion of the Fourth Doctor in the classic British science fiction television series Doctor Who.
  • D. Neeta
    Neeta is the tragic, self-sacrificing young woman at the center of Ritwik Ghatak’s classic Bengali film "Meghe Dhaka Tara."
  • E. Lasya
    Lasya is a graceful, expressive classical Indian dance style traditionally associated with feminine beauty and gentle, fluid movements.
  • 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_69d81c583b0081909e408a17db517a21 completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de02460a688190a27874f8d35819c7 completed April 14, 2026, 9 a.m.
NED1 Entity disambiguation (via context triple) batch_69f7b07670b08190a205d3c7ccb9dded completed May 3, 2026, 8:30 p.m.
NEDg Description generation batch_69f7b0f912f081908084042860c922cb completed May 3, 2026, 8:32 p.m.
NED2 Entity disambiguation (via description) batch_69f7b16a43188190968d5cdf32e447ec completed May 3, 2026, 8:34 p.m.
Created at: April 9, 2026, 10:11 p.m.