Triple
T15308809
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tell Tale |
E365973
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Dallas Roberts |
E594728
|
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: Dallas Roberts | Statement: [Tell Tale, stars, Dallas Roberts]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dallas Roberts Context triple: [Tell Tale, stars, Dallas Roberts]
-
A.
Dallas Roberts
chosen
Dallas Roberts is an American actor known for his versatile roles in film, television, and theater, including appearances in projects like "Dallas Buyers Club" and the series "The Walking Dead."
-
B.
Glenn Roberts
Glenn Roberts is an American grain expert and founder of Anson Mills, renowned for reviving heirloom Southern grains and rice varieties, including Carolina Gold rice.
-
C.
Larry Robinson
Larry Robinson is an American academic and administrator best known for serving as president of Florida A&M University.
-
D.
Larry Robinson
Larry Robinson is a Hall of Fame Canadian ice hockey defenseman best known for his long, successful career with the Montreal Canadiens and multiple Stanley Cup championships.
-
E.
Alan Osbiston
Alan Osbiston was a British film editor known for his work on notable mid-20th-century films, including major war and drama productions.
- 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_69d85a113ee881908e297a1d38dd79fa |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03cd176708190b0f6ba17aed92f8e |
completed | April 16, 2026, 1:35 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff5f2754648190bfd0bd15f20b40d2 |
completed | May 9, 2026, 4:21 p.m. |
Created at: April 10, 2026, 3:16 a.m.