Triple
T17489786
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I Take My Chances |
E425872
|
entity |
| Predicate | hasTitle |
P38
|
FINISHED |
| Object | I Take My Chances |
—
|
NE NERFINISHED |
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: I Take My Chances | Statement: [I Take My Chances, hasTitle, I Take My Chances]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: I Take My Chances Context triple: [I Take My Chances, hasTitle, I Take My Chances]
-
A.
I Take My Chances
chosen
"I Take My Chances" is a country song best known from its hit recording by Mary Chapin Carpenter, co-written with Don Schlitz, that reflects on risk, faith, and personal independence.
-
B.
Taking Chances
Taking Chances is a pop album by Canadian singer Celine Dion that marked her return to English-language studio recordings in the late 2000s.
-
C.
One Chance
One Chance is a 2013 British biographical comedy-drama film about opera singer Paul Potts, directed by David Frankel.
-
D.
One Chance
One Chance is an American R&B group best known for their mid-2000s work blending smooth harmonies with contemporary hip-hop-influenced production.
-
E.
Chances Are
"Chances Are" is a classic 1957 romantic pop ballad by Johnny Mathis that became one of his signature hits and a standard of the genre.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d889dccf7481909264a1844a2e9100 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451d461308190844c143dcfb61fac |
completed | April 19, 2026, 3:53 a.m. |
Created at: April 10, 2026, 5:48 a.m.