Triple
T110566
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Adventures of Tom Sawyer |
E2238
|
entity |
| Predicate | hasCharacter |
P2308
|
FINISHED |
| Object | Aunt Polly |
E11795
|
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: Aunt Polly | Statement: [The Adventures of Tom Sawyer, hasCharacter, Aunt Polly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aunt Polly Context triple: [The Adventures of Tom Sawyer, hasCharacter, Aunt Polly]
-
A.
Aunt Polly
chosen
Aunt Polly is Tom Sawyer’s strict but loving aunt and guardian in Mark Twain’s classic novel "The Adventures of Tom Sawyer."
-
B.
Aunt Eller
Aunt Eller is a plainspoken, good-humored farm matriarch who serves as a stabilizing, wisecracking presence in the musical "Oklahoma!".
-
C.
Becky Thatcher
Becky Thatcher is a spirited, kind-hearted girl in Mark Twain’s classic novel "The Adventures of Tom Sawyer," known as Tom’s love interest and a symbol of youthful innocence and adventure.
-
D.
Tom Sawyer
Tom Sawyer is a mischievous and imaginative boy from Mark Twain’s classic American novels, known for his adventurous exploits along the Mississippi River.
-
E.
Jem
Jem is a common diminutive or nickname for the given name James.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a256ce54b48190a3337f5f45d82859 |
completed | Feb. 28, 2026, 2:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a284fed06c81909df34f4227f26e7d |
completed | Feb. 28, 2026, 6:02 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.