Triple
T17851988
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yizhuang |
E445829
|
entity |
| Predicate | partOf |
P40
|
FINISHED |
| Object | Daxing District |
E89779
|
NE 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: Daxing District | Statement: [Yizhuang, partOf, Daxing District]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Daxing District Context triple: [Yizhuang, partOf, Daxing District]
-
A.
Daxing District
chosen
Daxing District is a rapidly developing suburban district in southern Beijing, China, known for hosting the major Beijing Daxing International Airport and large-scale urban expansion.
-
B.
Changping District
Changping District is a suburban district in the northern part of Beijing, China, known for its historical sites and scenic mountainous landscapes.
-
C.
Shunyi District
Shunyi District is a suburban district of Beijing known for hosting Beijing Capital International Airport and a mix of residential, industrial, and international community areas.
-
D.
Fangshan District
Fangshan District is a suburban district in the southwest of Beijing, China, known for its mix of residential areas, industrial zones, and historical and natural attractions.
-
E.
Haidian District
Haidian District is a major urban district in northwest Beijing known for its universities, technology hubs, and historic imperial gardens.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48fff6c288190a2b5e60b66c03ddc |
completed | April 19, 2026, 8:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a07b4d35f088190875264a509504dc7 |
completed | May 16, 2026, 12:05 a.m. |
Created at: April 10, 2026, 10:17 a.m.