Triple
T15699372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roy Munson |
E380552
|
entity |
| Predicate | theme |
P261
|
FINISHED |
| Object | second chances |
E1007629
|
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: second chances | Statement: [Roy Munson, theme, second chances]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: second chances Context triple: [Roy Munson, theme, second chances]
-
A.
Second Chances
chosen
Second Chances is a film featuring actor Matthew Salinger in its cast.
-
B.
Second Chances
Second Chances is a book authored by Patricia Southall that reflects her personal journey and insights on faith, resilience, and starting over.
-
C.
Second Chance
Second Chance is a 1953 American film noir crime drama notable for its early use of 3D technology and direction by Rudolph Maté.
-
D.
Second Chance
Second Chance is a science fiction crime drama television series that follows a resurrected former sheriff who uses his second life to help his son solve crimes.
-
E.
Second Chance
"Second Chance" is a popular rock ballad by the American band Shinedown, known for its introspective lyrics about personal growth and moving on from the past.
- 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_69d86d99e860819094b6957cde470f2c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f6d71308190971c10c599da9645 |
completed | April 16, 2026, 2:54 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff75756ecc8190bd2123ddfd080fd1 |
completed | May 9, 2026, 5:57 p.m. |
Created at: April 10, 2026, 4:44 a.m.