Triple
T3176757
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lutfunnisa Begum |
E66482
|
entity |
| Predicate | spouseReign |
P9813
|
FINISHED |
| Object | mid-18th century |
—
|
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: mid-18th century | Statement: [Lutfunnisa Begum, spouseReign, mid-18th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: spouseReign Context triple: [Lutfunnisa Begum, spouseReign, mid-18th century]
-
A.
monarchSpouseReignStart
Indicates the date when a monarch’s spouse began their role as consort during the monarch’s reign.
-
B.
marriedToFutureMonarch
Indicates that one person is married to another person who will become a monarch in the future.
-
C.
monarchConsortOf
chosen
Indicates that one person is the spouse of a reigning monarch, holding the role of consort to that monarch.
-
D.
spouseDynasty
Indicates that there is a marital relationship linking an entity to the dynasty (family line or ruling house) of their spouse.
-
E.
spouseOfHeadOfState
Indicates that one person is the spouse (married partner) of a head of state.
- 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_69ad8586a34c8190944c63ec11a8de1a |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada69b0bec8190957913b44d876079 |
completed | March 8, 2026, 4:40 p.m. |
| PD | Predicate disambiguation | batch_69ad9e02677c8190a21d93b1259b2761 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:06 p.m.