Triple
T14535994
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Donkey’s Christmas Shrektacular |
E341044
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Donkey |
E67941
|
NE FINISHED |
How this triple was built (2 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: Donkey | Statement: [Donkey’s Christmas Shrektacular, mainCharacter, Donkey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Donkey Context triple: [Donkey’s Christmas Shrektacular, mainCharacter, Donkey]
-
A.
Donkey (Shrek)
chosen
Donkey (Shrek) is the fast-talking, comedic, and loyal talking donkey who serves as Shrek’s sidekick in the Shrek animated film series.
-
B.
Dronkey
Dronkey is a fictional hybrid creature—half dragon, half donkey—from the Shrek film series, known as the offspring of Donkey and Dragon.
-
C.
Mule
Mule Suttles was a legendary power-hitting first baseman and outfielder in Negro league baseball, renowned for his prodigious home runs and later induction into the Baseball Hall of Fame.
-
D.
Kamel
Kamel is a given name, often used in Arabic-speaking and related cultures, that serves as a variant form of the name Kamal.
-
E.
Hank the Mule
Hank the Mule is a talking, often comically stubborn but loyal mule who accompanies Betsy Bobbin on her adventures in L. Frank Baum’s Oz series.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d822dac79c8190a84a073f3cbaced5 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb1b9d39881908c7a3a5b17d432af |
completed | April 14, 2026, 9:29 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fdd5c3d1d881909ed7e75aae7b08d9 |
completed | May 8, 2026, 12:23 p.m. |
Created at: April 10, 2026, 1:22 a.m.