Triple
T7993562
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Frances Clara Folsom |
E186066
|
entity |
| Predicate | ageAtStartOfFirstLadyRole |
P80226
|
FINISHED |
| Object | 21 |
—
|
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: 21 | Statement: [Frances Clara Folsom, ageAtStartOfFirstLadyRole, 21]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageAtStartOfFirstLadyRole Context triple: [Frances Clara Folsom, ageAtStartOfFirstLadyRole, 21]
-
A.
firstLadyTermApproximateStart
Indicates the approximate date when a person’s tenure as First Lady began.
-
B.
stateFirstLadyOf
Indicates that a person holds or has held the official role of First Lady for a given state.
-
C.
startTimeAsFirstLadyOfCalifornia
Indicates the date and time when an individual first assumed the role of First Lady of California.
-
D.
servedAsFirstLadyOfTheUnitedStatesFrom
Indicates that a person held the role of First Lady of the United States during a specified time period.
-
E.
hasFirstLadyMember
Indicates that an entity has, as a member, a woman who holds the role or title of First Lady.
- 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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c729afc81909d477b1623ac3f9d |
completed | March 31, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
| PDg | Predicate description generation | batch_69cb14bbbacc81909c6cf8ec35314bbb |
completed | March 31, 2026, 12:26 a.m. |
Created at: March 30, 2026, 5:16 p.m.