Triple
T3017297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Malaysia Airlines Flight 370 |
E82366
|
entity |
| Predicate | searchAreaRegion |
P2772
|
FINISHED |
| Object | southern Indian Ocean west of Australia |
—
|
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: southern Indian Ocean west of Australia | Statement: [Malaysia Airlines Flight 370, searchAreaRegion, southern Indian Ocean west of Australia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: searchAreaRegion Context triple: [Malaysia Airlines Flight 370, searchAreaRegion, southern Indian Ocean west of Australia]
-
A.
searchesRegion
chosen
Indicates that an entity performs a search operation within, or targeting, a specified geographic or administrative region.
-
B.
arealRegion
Indicates that something occupies or pertains to a specific two-dimensional geographic or spatial area.
-
C.
studiesRegion
Indicates that an entity engages in the academic or systematic study of a particular geographic or cultural region.
-
D.
countryRegion
Indicates that a country is located within, or belongs to, a specific geographic or administrative region.
-
E.
regionOfCity
Indicates that a specified area or district is a constituent part or subdivision of a particular city.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a90ea64819080620e60bbd6aa24 |
completed | March 8, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.