Triple
T16635191
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Three Ninjas |
E404179
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Tum-Tum
Tum-Tum is the youngest, food-loving and comedic brother in the Three Ninjas film series, known for his energetic personality and martial arts skills.
|
E1224164
|
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: Tum-Tum | Statement: [Three Ninjas, mainCharacter, Tum-Tum]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tum-Tum Context triple: [Three Ninjas, mainCharacter, Tum-Tum]
-
A.
Tutty
Tutty is a given name most notably associated with the fictional character Tutty Bomowski.
-
B.
Tubby
Tubby is the nickname of American college basketball coach Tubby Smith, known for leading the University of Kentucky to the 1998 NCAA championship.
-
C.
Brisky the Bear
Brisky the Bear is the costumed bear mascot of Japan’s Hokkaido Nippon-Ham Fighters professional baseball team, known for entertaining fans at games and team events.
-
D.
Tobo
Tobo is a small locality in eastern Sweden situated within Tierp Municipality in Uppsala County.
-
E.
Lippy the Lion
Lippy the Lion is a talkative, optimistic cartoon lion created by Hanna-Barbera who starred in early 1960s animated television shorts alongside his hyena sidekick Hardy Har Har.
- 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: Tum-Tum Triple: [Three Ninjas, mainCharacter, Tum-Tum]
Generated description
Tum-Tum is the youngest, food-loving and comedic brother in the Three Ninjas film series, known for his energetic personality and martial arts skills.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tum-Tum Target entity description: Tum-Tum is the youngest, food-loving and comedic brother in the Three Ninjas film series, known for his energetic personality and martial arts skills.
-
A.
Tutty
Tutty is a given name most notably associated with the fictional character Tutty Bomowski.
-
B.
Tubby
Tubby is the nickname of American college basketball coach Tubby Smith, known for leading the University of Kentucky to the 1998 NCAA championship.
-
C.
Brisky the Bear
Brisky the Bear is the costumed bear mascot of Japan’s Hokkaido Nippon-Ham Fighters professional baseball team, known for entertaining fans at games and team events.
-
D.
Tobo
Tobo is a small locality in eastern Sweden situated within Tierp Municipality in Uppsala County.
-
E.
Lippy the Lion
Lippy the Lion is a talkative, optimistic cartoon lion created by Hanna-Barbera who starred in early 1960s animated television shorts alongside his hyena sidekick Hardy Har Har.
- 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_69d8838a41f08190b0c3f79c47df5078 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e378e999d48190bff680040dbc883d |
completed | April 18, 2026, 12:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a007dc05bd881909c6b2e0d95622aa1 |
completed | May 10, 2026, 12:44 p.m. |
| NEDg | Description generation | batch_6a007e1909b88190ad2587b5d5433e2e |
completed | May 10, 2026, 12:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a007eda229c8190a6b99400141cf0b6 |
completed | May 10, 2026, 12:49 p.m. |
Created at: April 10, 2026, 5:17 a.m.