Triple
T1071200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Timor (western part) |
E23331
|
entity |
| Predicate | hasCoastlineOn |
P212
|
FINISHED |
| Object | Saw Sea |
E124161
|
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: Saw Sea | Statement: [Timor (western part), hasCoastlineOn, Saw Sea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saw Sea Context triple: [Timor (western part), hasCoastlineOn, Saw Sea]
-
A.
Saw Sea
chosen
The Saw Sea is a body of water located off the western part of Timor in Southeast Asia.
-
B.
Aquarium
The Aquarium at the Memphis Zoo is a dedicated exhibit showcasing a diverse collection of aquatic animals and ecosystems for education and public viewing.
-
C.
Sirena Deep
Sirena Deep is one of the deepest known points in the world's oceans, located within the Mariana Trench in the western Pacific Ocean.
-
D.
The Toll of the Sea
The Toll of the Sea is a 1922 silent drama film, one of the earliest Hollywood movies shot in Technicolor, featuring Anna May Wong in her first leading role.
-
E.
The Deep
The Deep is a 1976 adventure novel by Peter Benchley that follows a young couple who discover dangerous secrets and sunken treasure while diving near Bermuda.
- 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_69a493ee1f908190992b5f0d1b04459b |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b92848148190ba8795cb8d0a1d0a |
completed | March 1, 2026, 10:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac4c1fb7948190b08c95e68d3de00e |
completed | March 7, 2026, 4:02 p.m. |
Created at: March 1, 2026, 7:42 p.m.