Triple
T285642
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Claus |
E5879
|
entity |
| Predicate | notableReindeer |
P22
|
FINISHED |
| Object |
Prancer
Prancer is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
|
E37296
|
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: Prancer | Statement: [Santa Claus, notableReindeer, Prancer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Prancer Context triple: [Santa Claus, notableReindeer, Prancer]
-
A.
Jonathan the Husky
Jonathan the Husky is the costumed canine mascot representing the University of Connecticut and its athletic teams, including the renowned women’s basketball program.
-
B.
Barkley
Barkley is a surname most notably associated with Alben W. Barkley, the 35th vice president of the United States under President Harry S. Truman.
-
C.
Terry (dog)
Terry was the female Cairn Terrier best known for playing Toto in the 1939 film adaptation of "The Wizard of Oz."
-
D.
Kestrel
Kestrel is a pressure-fed, liquid-fueled rocket engine developed by SpaceX for the second stage of its early Falcon 1 launch vehicle.
-
E.
Polly
Polly is a ballad opera by John Gay, written as a sequel to his famous work "The Beggar's Opera" and noted for its satirical treatment of colonialism and morality.
- 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: Prancer Triple: [Santa Claus, notableReindeer, Prancer]
Generated description
Prancer is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Prancer Target entity description: Prancer is one of Santa Claus's legendary flying reindeer, traditionally depicted as helping pull his sleigh on Christmas Eve.
-
A.
Jonathan the Husky
Jonathan the Husky is the costumed canine mascot representing the University of Connecticut and its athletic teams, including the renowned women’s basketball program.
-
B.
Barkley
Barkley is a surname most notably associated with Alben W. Barkley, the 35th vice president of the United States under President Harry S. Truman.
-
C.
Terry (dog)
Terry was the female Cairn Terrier best known for playing Toto in the 1939 film adaptation of "The Wizard of Oz."
-
D.
Kestrel
Kestrel is a pressure-fed, liquid-fueled rocket engine developed by SpaceX for the second stage of its early Falcon 1 launch vehicle.
-
E.
Polly
Polly is a ballad opera by John Gay, written as a sequel to his famous work "The Beggar's Opera" and noted for its satirical treatment of colonialism and morality.
- 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_69a25946a7ac8190a78871c210213272 |
completed | Feb. 28, 2026, 2:56 a.m. |
| NER | Named-entity recognition | batch_69a260d21e5881909f3baba8b8dfff92 |
completed | Feb. 28, 2026, 3:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a39d078ad88190b4fce535c8ea9a80 |
completed | March 1, 2026, 1:57 a.m. |
| NEDg | Description generation | batch_69a39e93efc48190a1fa60d04ee7e85f |
completed | March 1, 2026, 2:04 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a39f38af0481908f0a3bfeda680065 |
completed | March 1, 2026, 2:06 a.m. |
Created at: Feb. 28, 2026, 3:02 a.m.