Triple
T18644369
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Animaniacs |
E455765
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object |
Buttons
Buttons is a loyal and overprotective dog character from the animated series "Animaniacs," often seen frantically safeguarding a young girl named Mindy from danger.
|
E1335188
|
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: Buttons | Statement: [Animaniacs, hasCharacter, Buttons]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buttons Context triple: [Animaniacs, hasCharacter, Buttons]
-
A.
Buttons
"Buttons" is a notable creative work by Sean Garrett, recognized as a key contribution to his career.
-
B.
Button
Button is a common English surname borne by various real and fictional individuals, including the character Benjamin Button.
-
C.
Button, Button
"Button, Button" is a suspenseful short story by Richard Matheson that explores moral dilemmas and the consequences of greed through a mysterious offer involving a deadly button.
-
D.
MatButton
MatButton is the Angular Material component that provides a styled, accessible button implementation consistent with the Material Design specification.
-
E.
BTN
BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
- 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: Buttons Triple: [Animaniacs, hasCharacter, Buttons]
Generated description
Buttons is a loyal and overprotective dog character from the animated series "Animaniacs," often seen frantically safeguarding a young girl named Mindy from danger.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Buttons Target entity description: Buttons is a loyal and overprotective dog character from the animated series "Animaniacs," often seen frantically safeguarding a young girl named Mindy from danger.
-
A.
Buttons
"Buttons" is a notable creative work by Sean Garrett, recognized as a key contribution to his career.
-
B.
Button
Button is a common English surname borne by various real and fictional individuals, including the character Benjamin Button.
-
C.
Button, Button
"Button, Button" is a suspenseful short story by Richard Matheson that explores moral dilemmas and the consequences of greed through a mysterious offer involving a deadly button.
-
D.
MatButton
MatButton is the Angular Material component that provides a styled, accessible button implementation consistent with the Material Design specification.
-
E.
BTN
BTN is the three-letter ISO 3166-1 alpha-3 country code assigned to Bhutan.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5500c36188190bfdd7aca73f3c006 |
completed | April 19, 2026, 9:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a050d865fc48190a11ed96ebfdca50d |
completed | May 13, 2026, 11:47 p.m. |
| NEDg | Description generation | batch_6a051058f5788190b782a39feb7f6111 |
completed | May 13, 2026, 11:59 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0510fc0d1081908970c91357bb3444 |
completed | May 14, 2026, 12:02 a.m. |
Created at: April 10, 2026, 11:47 a.m.