Triple
T2198355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Casey Affleck |
E50429
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Affleck |
E8985
|
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: Affleck | Statement: [Casey Affleck, familyName, Affleck]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Affleck Context triple: [Casey Affleck, familyName, Affleck]
-
A.
Afflecks
Afflecks is an iconic indoor market and alternative shopping emporium in Manchester known for its independent retailers, vintage fashion, and vibrant subcultural atmosphere.
-
B.
Ben Affleck
Ben Affleck is an American actor, director, and screenwriter known for films such as "Good Will Hunting," "Argo," and for portraying Batman in the DC Extended Universe.
-
C.
Casey Affleck
chosen
Casey Affleck is an American actor and filmmaker known for his understated, emotionally intense performances in films such as "Manchester by the Sea," for which he won the Academy Award for Best Actor.
-
D.
Michael Wahlberg
Michael Wahlberg is one of the children of American actor, producer, and former rapper Mark Wahlberg.
-
E.
Matt Damon
Matt Damon is an American actor, producer, and screenwriter known for his versatile performances in films such as Good Will Hunting, the Bourne series, and The Martian.
- 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_69a88b044ab48190add007487680f009 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abbf7b65cc8190bcc5a5c52b90f33b |
completed | March 7, 2026, 6:02 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5db9b0208190a63a75c86ea9dcff |
completed | March 9, 2026, 5:42 a.m. |
Created at: March 4, 2026, 7:46 p.m.