Triple
T7027094
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marble Mountains |
E162974
|
entity |
| Predicate | hasViewOf |
P854
|
FINISHED |
| Object | Da Nang Bay |
E616991
|
NE 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: Da Nang Bay | Statement: [Marble Mountains, hasViewOf, Da Nang Bay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Da Nang Bay Context triple: [Marble Mountains, hasViewOf, Da Nang Bay]
-
A.
Da Nang Bay
chosen
Da Nang Bay is a coastal bay in central Vietnam known for its scenic beaches, natural harbor, and proximity to the city of Da Nang.
-
B.
Phan Rang Bay
Phan Rang Bay is a coastal bay in south-central Vietnam known for its clear waters, sandy beaches, and proximity to the city of Phan Rang–Tháp Chàm.
-
C.
Vĩnh Hy Bay
Vĩnh Hy Bay is a scenic coastal bay in south-central Vietnam known for its clear blue waters, coral reefs, and surrounding rugged landscapes that make it a popular eco-tourism and sightseeing destination.
-
D.
Lan Ha Bay
Lan Ha Bay is a scenic bay in northern Vietnam known for its emerald waters, limestone karsts, and quieter, less-touristed alternative to nearby Ha Long Bay.
-
E.
Sepetiba Bay
Sepetiba Bay is a coastal bay in southeastern Brazil known for its rich marine biodiversity, fishing activities, and proximity to major industrial and port facilities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69c6885b26248190a857541e3d10e299 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6e1fd6ab48190865271e16e8ff669 |
completed | March 27, 2026, 8:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c77588285481909799a2bb76921b9a |
completed | March 28, 2026, 6:30 a.m. |
Created at: March 27, 2026, 2:35 p.m.