Triple
T19216937
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Segitiga Terumbu Karang |
E480509
|
entity |
| Predicate | terkaitDengan |
P37
|
FINISHED |
| Object | perikanan skala kecil di kawasan Asia Pasifik |
—
|
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: perikanan skala kecil di kawasan Asia Pasifik | Statement: [Segitiga Terumbu Karang, terkaitDengan, perikanan skala kecil di kawasan Asia Pasifik]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: terkaitDengan Context triple: [Segitiga Terumbu Karang, terkaitDengan, perikanan skala kecil di kawasan Asia Pasifik]
-
A.
relatedPass
Indicates that one pass is associated with or connected to another pass in some relevant way.
-
B.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
C.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
-
D.
moreCloselyRelatedTo
Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference entity.
-
E.
relatedToTerm
Indicates a general, non-specific relationship or association between one term and another.
- 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_69d8e8cb8c348190b52075823911c869 |
completed | April 10, 2026, 12:10 p.m. |
| NER | Named-entity recognition | batch_69e5fa3aff9c8190974363683b8246f5 |
completed | April 20, 2026, 10:04 a.m. |
| PD | Predicate disambiguation | batch_69e4dcf22b3c8190bee02e3af946e114 |
completed | April 19, 2026, 1:47 p.m. |
Created at: April 10, 2026, 1:23 p.m.