Triple
T7684905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Theodosia Burr Alston |
E174089
|
entity |
| Predicate | spouseGovernorshipStart |
P37616
|
FINISHED |
| Object | 1812 |
—
|
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: 1812 | Statement: [Theodosia Burr Alston, spouseGovernorshipStart, 1812]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseGovernorshipStart Context triple: [Theodosia Burr Alston, spouseGovernorshipStart, 1812]
-
A.
spousePositionHeldStartTime
chosen
Indicates the date and time when a spouse first began holding a particular position or office.
-
B.
spouseLaterOffice
Indicates that one person’s spouse held a particular office or position at a later time than the person in question.
-
C.
spouseOffice
Indicates that one entity holds an office or position that is associated with, or held by, the spouse of another entity.
-
D.
spouseStartTime
Indicates the point in time when two individuals began their spousal (marriage) relationship.
-
E.
servedAsGovernorUntil
Indicates that an entity held the position of governor up to a specified end date or time.
- 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_69c6995840408190a19de6c51090f46f |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c7048b0b448190889bd40e0a38e51a |
completed | March 27, 2026, 10:28 p.m. |
| PD | Predicate disambiguation | batch_69c701618d3481908be84b76f36ac5a1 |
completed | March 27, 2026, 10:14 p.m. |
Created at: March 27, 2026, 4:02 p.m.