Triple
T31949792
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 端门 |
E815747
|
entity |
| Predicate | 毗邻建筑 |
P77342
|
FINISHED |
| Object | 天安门 |
—
|
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: 天安门 | Statement: [端门, 毗邻建筑, 天安门]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 毗邻建筑 Context triple: [端门, 毗邻建筑, 天安门]
-
A.
hasNeighboringBuilding
chosen
Indicates that one building is located adjacent to or directly next to another building.
-
B.
adjacentBuildingFunction
Indicates that two buildings located next to each other have a specified functional relationship or usage connection.
-
C.
adjacentToInfrastructure
Indicates that one entity is located directly next to or in immediate proximity to a piece of infrastructure.
-
D.
hasMainBuildingNear
Indicates that the primary or central building associated with an entity is located in close physical proximity to another specified entity or place.
-
E.
architectOfSurroundingBuildings
Indicates that one entity is the architect responsible for designing the buildings that surround or are adjacent to another specified 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_69f348f42d188190a33fc8d20ec50517 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b2a905d081909cf5fbedd1181a1a |
completed | May 3, 2026, 2:27 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
Created at: May 1, 2026, 12:07 a.m.