Triple
T31355925
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sterns |
E799729
|
entity |
| Predicate | nameBeforeMarriageOf |
P36176
|
FINISHED |
| Object | Colleen Sterns Reagan |
—
|
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: Colleen Sterns Reagan | Statement: [Sterns, nameBeforeMarriageOf, Colleen Sterns Reagan]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nameBeforeMarriageOf Context triple: [Sterns, nameBeforeMarriageOf, Colleen Sterns Reagan]
-
A.
spouseNameAtMarriage
Indicates the full name a person’s spouse had at the time of their marriage.
-
B.
maidenNameOf
chosen
Indicates that one person’s original family surname before marriage is the maiden name of another person.
-
C.
laterMarriedName
Indicates that the referenced name is a surname or full name a person adopted after a later marriage, replacing or succeeding their previous name.
-
D.
eraNameOfSpouse
Indicates that the value is the name of the historical era associated with the spouse of the subject.
-
E.
namedForSpouse
Indicates that one entity is named after the spouse of another entity.
- F. None of above.
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_69f224e5e9bc8190a16339328897c4f8 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f470e8c8190a92ac1c47877bafc |
completed | May 3, 2026, 1:05 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:17 p.m.