Triple
T7708076
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Doris Sydnor |
E174672
|
entity |
| Predicate | maritalPeriodWith |
P78262
|
FINISHED |
| Object | final years of Charlie Parker's life |
—
|
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: final years of Charlie Parker's life | Statement: [Doris Sydnor, maritalPeriodWith, final years of Charlie Parker's life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritalPeriodWith Context triple: [Doris Sydnor, maritalPeriodWith, final years of Charlie Parker's life]
-
A.
marriageDuration
Indicates the length of time that a marriage relationship has existed between two spouses.
-
B.
marriedBy
Indicates that one entity is the officiant or authority who performs and formalizes the marriage of another entity.
-
C.
marriedIn
Indicates that two entities entered into a marital relationship at a specific place or within a particular jurisdiction.
-
D.
roleDuringSpouseTenure
Indicates that a person held a particular role or position specifically during the period when their spouse was in office or serving in a defined tenure.
-
E.
marriedAfter
Indicates that one marriage occurred later in time than another specified marriage.
- 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_69c6995b3e8c8190833108f883d5f53c |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c702ebb7448190ae8d47fe0cbb0907 |
completed | March 27, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69c701683dec8190be9861e592aa8ce0 |
completed | March 27, 2026, 10:15 p.m. |
| PDg | Predicate description generation | batch_69c702e9a32081909a153190a62af426 |
completed | March 27, 2026, 10:21 p.m. |
Created at: March 27, 2026, 4:04 p.m.