Triple

T11824608
Position Surface form Disambiguated ID Type / Status
Subject Rikki-Tikki-Tavi E281226 entity
Predicate protects P1040 FINISHED
Object Teddy
Teddy is the young English boy in Rudyard Kipling’s story “Rikki-Tikki-Tavi,” whose life is saved from deadly cobras by the brave mongoose.
 E948472 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: Teddy | Statement: [Rikki-Tikki-Tavi, protects, Teddy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Teddy
Context triple: [Rikki-Tikki-Tavi, protects, Teddy]
  • A. Teddy
    Teddy is Mr. Bean’s beloved brown teddy bear, a silent yet expressive companion that often serves as his confidant and playmate in the comedy series.
  • B. Teddy
    Teddy is a character in Louisa May Alcott’s novel "Jo’s Boys," part of the continuation of the March family saga begun in "Little Women."
  • C. Teddy
    Teddy is the nickname of Teddy Kollek, the long-serving and influential former mayor of Jerusalem.
  • D. Teddy
    Teddy is a key supporting character in the film "Memento," serving as a dubious ally whose true motives and identity are gradually revealed through the story's nonlinear narrative.
  • E. Teddy
    Teddy is a recurring character on the animated TV show "Bob's Burgers," known as the Belcher family's loyal but somewhat bumbling handyman and regular customer.
  • 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: Teddy
Triple: [Rikki-Tikki-Tavi, protects, Teddy]
Generated description
Teddy is the young English boy in Rudyard Kipling’s story “Rikki-Tikki-Tavi,” whose life is saved from deadly cobras by the brave mongoose.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Teddy
Target entity description: Teddy is the young English boy in Rudyard Kipling’s story “Rikki-Tikki-Tavi,” whose life is saved from deadly cobras by the brave mongoose.
  • A. Teddy
    Teddy is Mr. Bean’s beloved brown teddy bear, a silent yet expressive companion that often serves as his confidant and playmate in the comedy series.
  • B. Teddy
    Teddy is a character in Louisa May Alcott’s novel "Jo’s Boys," part of the continuation of the March family saga begun in "Little Women."
  • C. Teddy
    Teddy is a recurring character on the animated TV show "Bob's Burgers," known as the Belcher family's loyal but somewhat bumbling handyman and regular customer.
  • D. Teddy
    Teddy is the nickname of Teddy Kollek, the long-serving and influential former mayor of Jerusalem.
  • E. Teddy
    Teddy is a key supporting character in the film "Memento," serving as a dubious ally whose true motives and identity are gradually revealed through the story's nonlinear narrative.
  • 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_69d6ab276f8c8190b1966a0ef11349ac completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a5eb299481909de3c0e85628fbe4 completed April 10, 2026, 7:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69f131f4e2ec8190a78c101e17eaa5c0 completed April 28, 2026, 10:17 p.m.
NEDg Description generation batch_69f14e8ada3481908ec456c41827160c completed April 29, 2026, 12:19 a.m.
NED2 Entity disambiguation (via description) batch_69f1571e4ba08190824db812ffc5f35a completed April 29, 2026, 12:55 a.m.
Created at: April 8, 2026, 9:43 p.m.