Triple
T1615828
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christmas Island |
E34715
|
entity |
| Predicate | percentageProtectedArea |
P30455
|
FINISHED |
| Object | over 60 percent of island |
—
|
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: over 60 percent of island | Statement: [Christmas Island, percentageProtectedArea, over 60 percent of island]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: percentageProtectedArea Context triple: [Christmas Island, percentageProtectedArea, over 60 percent of island]
-
A.
hasProtectedAreaStatus
Indicates that an area is officially designated and managed as a protected area under relevant conservation or legal frameworks.
-
B.
protectedAreaCountry
Indicates that a protected area is located within and legally falls under the jurisdiction of a specific country.
-
C.
hasProtectedArea
Indicates that an entity possesses, includes, or is associated with a designated protected area for conservation or restricted use.
-
D.
partOfProtectedAreaCategory
Indicates that one protected area belongs to, or is classified under, a specific protected area category.
-
E.
percentageOfLandInNationalPark
Indicates the proportion of a given area’s total land that lies within designated national park boundaries.
- 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_69a885ffc5ec819091afa325d5f9611c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a93fef600c819080fe75c42c8e6dac |
completed | March 5, 2026, 8:33 a.m. |
| PD | Predicate disambiguation | batch_69a907c52a548190b648a31ea306dd5b |
completed | March 5, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69a93fedcb108190ad91f938d5eeaaa2 |
completed | March 5, 2026, 8:33 a.m. |
Created at: March 4, 2026, 7:28 p.m.