Triple
T19520897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Barnyard |
E488397
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object |
Pip
Pip is a young, adventurous mouse from the animated film "Barnyard," known for his quick wit and loyal friendship with the barnyard animals.
|
E1380253
|
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: Pip | Statement: [Barnyard, mainCharacter, Pip]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pip Context triple: [Barnyard, mainCharacter, Pip]
-
A.
Pip
Pip is a young Black cabin boy aboard the Pequod in Herman Melville’s novel "Moby-Dick," whose traumatic experience at sea leads to a profound, prophetic madness.
-
B.
Pip
Pip is the orphaned protagonist and narrator of Charles Dickens's novel "Great Expectations," whose life traces a journey from humble beginnings to social ambition and moral self-discovery.
-
C.
Pip Tyler
Pip Tyler is the troubled, idealistic young woman who serves as the central protagonist of Jonathan Franzen’s novel "Purity."
-
D.
Mr. Dick
Mr. Dick is an eccentric but kind-hearted and loyal companion in Charles Dickens's novel "David Copperfield," known for his childlike simplicity and devotion to Betsey Trotwood.
-
E.
Pip Pearce
Pip Pearce is an actor known for his role in the horror film "The Woman in Black 2: Angel of Death."
- 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: Pip Triple: [Barnyard, mainCharacter, Pip]
Generated description
Pip is a young, adventurous mouse from the animated film "Barnyard," known for his quick wit and loyal friendship with the barnyard animals.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Pip Target entity description: Pip is a young, adventurous mouse from the animated film "Barnyard," known for his quick wit and loyal friendship with the barnyard animals.
-
A.
Pip
Pip is a young Black cabin boy aboard the Pequod in Herman Melville’s novel "Moby-Dick," whose traumatic experience at sea leads to a profound, prophetic madness.
-
B.
Pip
Pip is the orphaned protagonist and narrator of Charles Dickens's novel "Great Expectations," whose life traces a journey from humble beginnings to social ambition and moral self-discovery.
-
C.
Pip Tyler
Pip Tyler is the troubled, idealistic young woman who serves as the central protagonist of Jonathan Franzen’s novel "Purity."
-
D.
Mr. Dick
Mr. Dick is an eccentric but kind-hearted and loyal companion in Charles Dickens's novel "David Copperfield," known for his childlike simplicity and devotion to Betsey Trotwood.
-
E.
Pip Pearce
Pip Pearce is an actor known for his role in the horror film "The Woman in Black 2: Angel of Death."
- 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_69d8e8da8bec819081f400199491ccc3 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e635a0b37c8190b70b7427c2e85f59 |
completed | April 20, 2026, 2:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07472af0b881909e5bada0955b52bb |
completed | May 15, 2026, 4:17 p.m. |
| NEDg | Description generation | batch_6a0747f6b1d48190a3e70576ddb4feb2 |
completed | May 15, 2026, 4:21 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a07492259488190a8c405598f9c8878 |
completed | May 15, 2026, 4:26 p.m. |
Created at: April 10, 2026, 1:40 p.m.