Triple
T12598595
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Angelina |
E300797
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Angeline |
E719910
|
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: Angeline | Statement: [Angelina, hasVariant, Angeline]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Angeline Context triple: [Angelina, hasVariant, Angeline]
-
A.
Angeline
chosen
Angeline is the given name of American actress Angie Dickinson, known for her roles in film and television from the 1950s onward.
-
B.
Angela
Angela is the given name of Angela Merkel, the long-serving former Chancellor of Germany and a prominent European political leader.
-
C.
Angela
Angela is the heroine of Matthew Lewis's Gothic melodrama "The Castle Spectre," central to its tale of mystery, romance, and supernatural intrigue.
-
D.
Angela
Angela is the Italian surname of the prominent scientific popularizer and television host Piero Angela.
-
E.
Angela
Angela is a character in the British stage play and film "Abigail's Party," known for her polite, somewhat naive demeanor amid the story's tense social dynamics.
- 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_69d7bdea2ca881908f379526c13b1145 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d954d096d08190afa1f685bad68d35 |
completed | April 10, 2026, 7:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f671926a7c8190a41725cfde7836b1 |
completed | May 2, 2026, 9:50 p.m. |
Created at: April 9, 2026, 5:09 p.m.