Triple
T32495509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Houyuan |
E830510
|
entity |
| Predicate | endYearInChineseCalendar |
P214
|
FINISHED |
| Object | the 2nd year of Houyuan (yihai year) |
—
|
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: the 2nd year of Houyuan (yihai year) | Statement: [Houyuan, endYearInChineseCalendar, the 2nd year of Houyuan (yihai year)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: endYearInChineseCalendar Context triple: [Houyuan, endYearInChineseCalendar, the 2nd year of Houyuan (yihai year)]
-
A.
timeInChineseEraSystem
Indicates that a temporal reference is expressed using a specific Chinese era-based calendrical system (such as reign titles or traditional era names).
-
B.
endYear
chosen
Indicates the year in which an event, state, or relationship comes to an end.
-
C.
unifiedChinaInYear
Indicates that the subject brought all of China under a single political authority in the specified year.
-
D.
usedChineseEraNames
Indicates that one entity employed or referenced Chinese era names in relation to another entity or context.
-
E.
usesSexagenaryCycleFor
Indicates that something is organized, measured, or represented using the traditional sexagenary (base-60) cyclical system.
- 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_69f349219cb8819087e120f509629c1b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c8159edc8190b1c87015e0c820e8 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 12:59 a.m.