Triple
T31981372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One More Chance |
E816588
|
entity |
| Predicate | previousSingleYear |
P197420
|
FINISHED |
| Object | 2009 |
—
|
LITERAL 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: 2009 | Statement: [One More Chance, previousSingleYear, 2009]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: previousSingleYear Context triple: [One More Chance, previousSingleYear, 2009]
-
A.
previousEventYear
Indicates that one event occurred in a year that is earlier than the year of another event.
-
B.
previousMatchYear
Indicates that one event or match occurred in the year immediately preceding the year of another event or match.
-
C.
previousTourYear
Indicates that one entity’s tour took place in the year immediately preceding the year of another specified tour.
-
D.
previousElectionYear
Indicates the year in which the immediately preceding election for the same office, position, or body took place.
-
E.
pastSettingYear
Indicates that an event, narrative, or situation is set in or associated with a specific year in the past.
- F. None of above. chosen
Provenance (4 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_69f348f6a3008190bfb59ca695fd68e2 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fe91383a1c81909266e40c3c3ede6c |
completed | May 9, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69fe8fde094081908f0f121664fbb5c7 |
completed | May 9, 2026, 1:37 a.m. |
| PDg | Predicate description generation | batch_69fe9137730c81909d1d57c30566c89a |
completed | May 9, 2026, 1:43 a.m. |
Created at: May 1, 2026, 12:11 a.m.