Triple
T36379466
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chunqiu |
E896003
|
entity |
| Predicate | coversHistoricalPeriod |
P59380
|
FINISHED |
| Object | Spring and Autumn period |
—
|
NE NERFINISHED |
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: Spring and Autumn period | Statement: [Chunqiu, coversHistoricalPeriod, Spring and Autumn period]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversHistoricalPeriod Context triple: [Chunqiu, coversHistoricalPeriod, Spring and Autumn period]
-
A.
historicalDocumentationPeriod
Indicates the time span during which something is documented or recorded in historical sources.
-
B.
historicalIntroductionPeriod
Indicates the time period during which something was first introduced or came into use in a historical context.
-
C.
historicalPeriodOfSignificance
Indicates the time period during which an entity is considered to have had its most important or influential historical impact.
-
D.
historicallyEncompassed
chosen
Indicates that one entity previously included, covered, or contained another entity within its scope, extent, or boundaries during a past historical period.
-
E.
occupationPeriod
Indicates the time span during which an entity holds or held a particular occupation or role.
- 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_69f76e51d358819092bbc5f119f49476 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
Created at: May 3, 2026, 4:10 p.m.