Triple
T25929120
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madagascar dry deciduous forests |
E653385
|
entity |
| Predicate | protectedAreaExample |
P86799
|
FINISHED |
| Object | Ankarafantsika National Park |
—
|
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: Ankarafantsika National Park | Statement: [Madagascar dry deciduous forests, protectedAreaExample, Ankarafantsika National Park]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: protectedAreaExample Context triple: [Madagascar dry deciduous forests, protectedAreaExample, Ankarafantsika National Park]
-
A.
protectedAreaCore
Indicates that an entity lies within the core, most strictly protected zone of a designated protected area.
-
B.
protectedAreaName
Indicates the designated name assigned to a protected area.
-
C.
protectedAreaCountry
Indicates that a protected area is located within and legally falls under the jurisdiction of a specific country.
-
D.
protectedAreaGateway
Indicates that an entity serves as an entrance or access point leading into a protected or restricted area.
-
E.
protectedAreaAssociation
chosen
Indicates an association where one entity is designated as, or linked to, a protected area in relation to another 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_69e7ab3eb9b881909c1390690551f868 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f6041710b481909f9583a3bbe16475 |
completed | May 2, 2026, 2:03 p.m. |
| PD | Predicate disambiguation | batch_69f602d07590819085ac34b189613104 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 22, 2026, 8:36 a.m.