Triple
T2699216
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hong Kong–Zhuhai–Macau Bridge |
E58588
|
entity |
| Predicate | numberOfArtificialIslands |
P42051
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Hong Kong–Zhuhai–Macau Bridge, numberOfArtificialIslands, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfArtificialIslands Context triple: [Hong Kong–Zhuhai–Macau Bridge, numberOfArtificialIslands, 3]
-
A.
numberOfIslands
Indicates the total count of distinct, separate landmasses (islands) present within a given area or context.
-
B.
nearestLargeIsland
Indicates that one entity is the closest geographically among all islands considered "large" relative to another reference entity.
-
C.
hasNumberOfInhabitedIslands
Indicates the relationship that specifies how many islands within a given area or jurisdiction are inhabited.
-
D.
hasNumberOfMajorIslands
Indicates the quantitative relationship specifying how many major islands are associated with a given entity.
-
E.
islandSize
Indicates the size or area measurement associated with a particular island.
- F. None of above. chosen
Provenance (4 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_69ab4ac269e481909cb317d79e68b75b |
completed | March 6, 2026, 9:44 p.m. |
| NER | Named-entity recognition | batch_69abda339cf48190b9ae6b99137f005e |
completed | March 7, 2026, 7:56 a.m. |
| PD | Predicate disambiguation | batch_69abd82062988190b4292f242ad70b2c |
completed | March 7, 2026, 7:47 a.m. |
| PDg | Predicate description generation | batch_69abd9ceec708190aa162399023b2273 |
completed | March 7, 2026, 7:54 a.m. |
Created at: March 6, 2026, 9:55 p.m.