Triple
T9692799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 天安门 |
E234574
|
entity |
| Predicate | 重要事件 |
P259
|
FINISHED |
| Object | 1949年10月1日中华人民共和国开国大典举行地点的城楼 |
—
|
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: 1949年10月1日中华人民共和国开国大典举行地点的城楼 | Statement: [天安门, 重要事件, 1949年10月1日中华人民共和国开国大典举行地点的城楼]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 重要事件 Context triple: [天安门, 重要事件, 1949年10月1日中华人民共和国开国大典举行地点的城楼]
-
A.
significantEventType
Indicates the specific category or kind of major or noteworthy event associated with an entity or situation.
-
B.
significantEvent
chosen
Indicates that an event involving the entities is of notable importance or impact within a given context.
-
C.
significantEventEnd
Indicates the point in time when a significant event or occurrence comes to a close or is considered finished.
-
D.
impactEvent
Indicates that one entity physically strikes or collides with another, producing a resulting effect or change.
-
E.
importantSaint
Indicates that the subject is recognized as a particularly significant or highly revered saint within a religious or spiritual tradition.
- 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_69ca84cb580c8190a7e5f4b3bcdaf2a4 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9d0727908190897894151c0ee7c2 |
completed | April 1, 2026, 10:32 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:17 p.m.