Triple
T16061009
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Noble Consort Yi |
E389610
|
entity |
| Predicate | reignAsEmpressDowagerStart |
P121473
|
FINISHED |
| Object | 1861 |
—
|
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: 1861 | Statement: [Noble Consort Yi, reignAsEmpressDowagerStart, 1861]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: reignAsEmpressDowagerStart Context triple: [Noble Consort Yi, reignAsEmpressDowagerStart, 1861]
-
A.
reignAsEmpressConsortBegan
Indicates the point in time when an individual began their tenure or role as an empress consort.
-
B.
realmAsEmpress
Indicates that an entity holds the position or role of empress over a specified realm or domain.
-
C.
reignAsRegentStart
Indicates the point in time when an individual begins exercising ruling authority as a regent on behalf of another.
-
D.
eraAsEmpress
Indicates the time period during which a person held the role or status of empress.
-
E.
successorAsEmpress
Indicates that one person became the next empress following another, directly succeeding her in that imperial role.
- 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_69d86dae698881908327ef2d67706cb9 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1858a00888190b8505071575dc56f |
completed | April 17, 2026, 12:57 a.m. |
| PD | Predicate disambiguation | batch_69e18272f2288190a17d45fb01cc2b07 |
completed | April 17, 2026, 12:44 a.m. |
| PDg | Predicate description generation | batch_69e185879c10819080a18e24969b5a6d |
completed | April 17, 2026, 12:57 a.m. |
Created at: April 10, 2026, 4:57 a.m.