Triple
T3056298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hocus Pocus |
E60487
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Allison |
E136320
|
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: Allison | Statement: [Hocus Pocus, character, Allison]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Allison Context triple: [Hocus Pocus, character, Allison]
-
A.
Alison
chosen
Alison is a feminine given name of English origin, commonly used in many English-speaking countries.
-
B.
Allegra Stratton
Allegra Stratton is a British journalist and former Downing Street press secretary known for her work in political communications and broadcasting.
-
C.
Allie Sherman
Allie Sherman was an American football coach best known for leading the New York Giants in the early 1960s, guiding them to multiple NFL Championship Game appearances.
-
D.
Ashley
Ashley is a character featured in the animated children’s series "¡Dos!"
-
E.
Ashley
Ashley is a given name commonly used in English-speaking countries for both males and females.
- 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_69ad8578137c81908259dcb27c7d6d7c |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ad9bf7ebd48190ad5748a18fa9a56a |
completed | March 8, 2026, 3:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b1f8759f988190a69ca8a4682af5ba |
completed | March 11, 2026, 11:19 p.m. |
Created at: March 8, 2026, 3:02 p.m.