Triple
T8501419
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | To Kill a Mockingbird (1962 film) |
E201225
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Phillip Alford |
E712037
|
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: Phillip Alford | Statement: [To Kill a Mockingbird (1962 film), starring, Phillip Alford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phillip Alford Context triple: [To Kill a Mockingbird (1962 film), starring, Phillip Alford]
-
A.
Phillip Alford
chosen
Phillip Alford is an American former child actor best known for his role as Jem Finch in the classic film "To Kill a Mockingbird."
-
B.
Phillip Reed
Phillip Reed was an American film and television actor active primarily in the mid-20th century, known for his roles in crime dramas and adventure films.
-
C.
Tony Puryear
Tony Puryear is an American screenwriter best known for co-writing the 1996 action film "Eraser" starring Arnold Schwarzenegger.
-
D.
Grant Bardsley
Grant Bardsley is a British voice actor best known for voicing the protagonist Taran in Disney’s animated film "The Black Cauldron."
-
E.
Randy Bricker
Randy Bricker is a film editor known for his work on horror and genre films, including Texas Chainsaw 3D.
- 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_69ca831fe47c8190b5c57b456d2aefa0 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe59ad65c8190a2b8e6d22269853a |
completed | March 31, 2026, 3:17 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce88e0e08c819085d29157349a6ef6 |
completed | April 2, 2026, 3:18 p.m. |
Created at: March 30, 2026, 6:14 p.m.