Triple
T16912514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Empress Xiaoduanxian |
E410235
|
entity |
| Predicate | marriageToWanliYear |
P125193
|
FINISHED |
| Object | 1578 |
—
|
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: 1578 | Statement: [Empress Xiaoduanxian, marriageToWanliYear, 1578]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: marriageToWanliYear Context triple: [Empress Xiaoduanxian, marriageToWanliYear, 1578]
-
A.
marriedToEmperor
Indicates that one entity is the spouse of an emperor, signifying a marital relationship to a reigning or titled emperor.
-
B.
marriageFormedBy
Indicates that a marriage relationship was created or brought into existence by a specific event, action, or process.
-
C.
betrothalYear
Indicates the year in which two entities became formally engaged to be married.
-
D.
marriageToFrancisIOfAustriaStart
Indicates the point in time when an entity’s marriage to Francis I of Austria begins.
-
E.
marriedInYear
Indicates that two entities are married to each other in a specific calendar year.
- 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_69d886c7b1e481908c3766dfa8c13458 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3ca3e6b9481909fbaeb0bddd7e3b2 |
completed | April 18, 2026, 6:15 p.m. |
| PD | Predicate disambiguation | batch_69e32b9489408190bcb2ede567ff5bf9 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e34fb7c8c8819086975b7955b7d8ef |
completed | April 18, 2026, 9:32 a.m. |
Created at: April 10, 2026, 5:30 a.m.