Triple
T28489682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zhuhai urban transport network |
E720926
|
entity |
| Predicate | connectsKeyLocation |
P51738
|
FINISHED |
| Object | Gongbei district |
—
|
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: Gongbei district | Statement: [Zhuhai urban transport network, connectsKeyLocation, Gongbei district]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: connectsKeyLocation Context triple: [Zhuhai urban transport network, connectsKeyLocation, Gongbei district]
-
A.
connectsLocation
chosen
Indicates a relationship where one entity serves as a link or route that joins or provides access between two locations.
-
B.
connectsKeyHub
Indicates that one entity serves as a key hub that links or routes connections between multiple other entities.
-
C.
connectionLocation
Indicates the place or spatial context where a connection between entities occurs or is established.
-
D.
connectsKeyDestinationsIn
Indicates that something serves as a link or route joining important or primary destinations within a specified area or context.
-
E.
connectsKeyDistrict
Indicates that one entity establishes or maintains a significant linkage or route to a strategically important or central district.
- 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_69f01a5a47148190b0a7e111bc432e0a |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69fd553d7cb881908d243e7a9f30ac85 |
completed | May 8, 2026, 3:15 a.m. |
| PD | Predicate disambiguation | batch_69fd514dcb1c81908333c70d7edd79c9 |
completed | May 8, 2026, 2:58 a.m. |
Created at: April 28, 2026, 3 a.m.