Triple
T13672943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Café Society |
E327796
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Anna Camp |
E454459
|
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: Anna Camp | Statement: [Café Society, starredActor, Anna Camp]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anna Camp Context triple: [Café Society, starredActor, Anna Camp]
-
A.
Anna Camp
chosen
Anna Camp is an American actress and singer best known for her roles in the Pitch Perfect film series and television shows such as True Blood and The Mindy Project.
-
B.
Melissa Cobb
Melissa Cobb is an American film producer best known for her work on major animated features, including the Kung Fu Panda franchise.
-
C.
Alice Patten
Alice Patten is a British actress best known internationally for her role as an English documentary filmmaker in the acclaimed Indian film "Rang De Basanti."
-
D.
Allison Mack
Allison Mack is an American actress best known for her role as Chloe Sullivan on the television series "Smallville."
-
E.
Karen Rodriguez
Karen Rodriguez is an actress known for her role in the television series "Swarm."
- 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_69d8076f1fa8819094664a59b55010df |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc65aab348190a6611f5765f8392d |
completed | April 12, 2026, 4:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce6254e88190b6b4541fa22dc508 |
completed | May 3, 2026, 10:38 p.m. |
Created at: April 9, 2026, 9:53 p.m.