Triple
T26772941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Paloma Cordero |
E670030
|
entity |
| Predicate | spouseEndTimeAsPresident |
P70424
|
FINISHED |
| Object | 1988 |
—
|
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: 1988 | Statement: [Paloma Cordero, spouseEndTimeAsPresident, 1988]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseEndTimeAsPresident Context triple: [Paloma Cordero, spouseEndTimeAsPresident, 1988]
-
A.
spouseOfficeEndTime
chosen
Indicates the time at which a spouse’s term or tenure in a particular office or position ends.
-
B.
spouseEndTime
Indicates the time or date at which a spousal relationship between two entities ends.
-
C.
spouseNumberOfTermsInOffice
Indicates the number of distinct terms in office that the spouse of the referenced entity has served.
-
D.
marriedToDuringOffice
Indicates that one person was married to another person specifically during the time they held a particular office or position.
-
E.
marriedToVicePresident
Indicates that one person is legally married to an individual who holds the office or role of vice president.
- 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_69eeb31c925881909b597f6e40056d28 |
completed | April 27, 2026, 12:51 a.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 27, 2026, 4:03 a.m.