Triple
T14765593
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Teen Wolf Too |
E346984
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Paul Sand |
E1096652
|
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: Paul Sand | Statement: [Teen Wolf Too, starring, Paul Sand]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Paul Sand Context triple: [Teen Wolf Too, starring, Paul Sand]
-
A.
Paul Sand
chosen
Paul Sand is an American actor and comedian known for his work in film, television, and theater, particularly during the 1970s and 1980s.
-
B.
Stanley Hoffman
Stanley Hoffman is a notable individual distinguished enough to be recognized as a prominent bearer of the surname Hoffman.
-
C.
Sam Fields
Sam Fields is known primarily as the husband of acclaimed American film editor Verna Fields.
-
D.
Dean Jones
Dean Jones was an American actor best known for his leading roles in numerous Disney live-action films during the 1960s and 1970s.
-
E.
Louis Begley
Louis Begley is a Polish-born American novelist and lawyer best known for his critically acclaimed works exploring identity, morality, and the legacy of the Holocaust.
- 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_69d822e8896c819091169882f9b20486 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7f576c881909da70627f5897c94 |
completed | April 14, 2026, 11:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe0cf4cef081909fa62125f43b36bc |
completed | May 8, 2026, 4:19 p.m. |
Created at: April 10, 2026, 1:30 a.m.