Triple
T9354879
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margarita Maza de Juárez |
E225112
|
entity |
| Predicate | startTime (position: First Lady of Mexico) |
P88105
|
FINISHED |
| Object | 1858 |
—
|
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: 1858 | Statement: [Margarita Maza de Juárez, startTime (position: First Lady of Mexico), 1858]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: startTime (position: First Lady of Mexico) Context triple: [Margarita Maza de Juárez, startTime (position: First Lady of Mexico), 1858]
-
A.
startTime (position: First Lady of the Confederate States of America)
Indicates the date and time at which a person began serving in the position of First Lady of the Confederate States of America.
-
B.
startTimeAsFirstLadyOfCalifornia
Indicates the date and time when an individual first assumed the role of First Lady of California.
-
C.
ageAtStartOfFirstLadyRole
Indicates the age a person was when they first assumed the role of First Lady.
-
D.
firstLadyTermApproximateStart
Indicates the approximate date when a person’s tenure as First Lady began.
-
E.
endTimeAsFirstLadyOfCalifornia
Indicates the date and time when an individual's tenure as First Lady of California comes to an end.
- 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_69ca842abfd48190949d71c3b86eeba8 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4f99205c8190a5ad95926ef25497 |
completed | April 1, 2026, 5:02 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
| PDg | Predicate description generation | batch_69cc955a38108190b602d1e73725f11b |
completed | April 1, 2026, 3:47 a.m. |
Created at: March 30, 2026, 7:42 p.m.