Triple
T13914671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 午门 |
E334588
|
entity |
| Predicate | 与天安门关系 |
P57645
|
FINISHED |
| Object | 位于天安门以北 |
—
|
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: 位于天安门以北 | Statement: [午门, 与天安门关系, 位于天安门以北]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 与天安门关系 Context triple: [午门, 与天安门关系, 位于天安门以北]
-
A.
相关城市地标
Indicates a relationship where a city landmark is associated with, connected to, or relevant to a given entity or context.
-
B.
roleInCaptureOfBeijing
Indicates the role or involvement an entity had in the capture of Beijing.
-
C.
国の象徴との関係
Indicates a relationship or association that an entity has with a national symbol (such as a flag, emblem, or anthem).
-
D.
isPartOfCrossStraitRelations
Indicates that something belongs to, affects, or is involved in the political, economic, social, or cultural interactions and dynamics between the two sides of the Taiwan Strait.
-
E.
notableBuildingAssociated
chosen
Indicates a relationship where a notable or significant building is associated with, connected to, or relevant to a given entity.
- 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_69d81c5eaa9c819083b1ff8689179565 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de27245c648190b2946845ce0fdbf8 |
completed | April 14, 2026, 11:38 a.m. |
| PD | Predicate disambiguation | batch_69de059e4ba881908554f72e889719fa |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:16 p.m.