Triple
T62314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bermuda Triangle |
E1237
|
entity |
| Predicate | airTraffic |
P4589
|
FINISHED |
| Object | frequent commercial and private flights |
—
|
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: frequent commercial and private flights | Statement: [Bermuda Triangle, airTraffic, frequent commercial and private flights]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airTraffic Context triple: [Bermuda Triangle, airTraffic, frequent commercial and private flights]
-
A.
FAAcode
Indicates that an entity (such as an airport or facility) is associated with a specific identifying code assigned by the Federal Aviation Administration (FAA).
-
B.
containsAirfield
Indicates that a location or area includes at least one airfield within its boundaries.
-
C.
peakPassengerTrafficRank
Indicates the relative position of an entity in an ordered list based on the amount of passenger traffic it experiences at its peak.
-
D.
peakFreightTrafficRank
Indicates the relative ranking position of an entity based on the highest level of freight traffic it experiences or handles compared to others.
-
E.
aircraft
Indicates that an entity is an aircraft or functions in the role of an aircraft in the described context.
- F. None of above. chosen
Provenance (4 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_69a24ba4f760819081f6638a3c70538a |
completed | Feb. 28, 2026, 1:57 a.m. |
| NER | Named-entity recognition | batch_69a251f74b0881909ad89127b8171277 |
completed | Feb. 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69a24ea242c8819086fe00bf01e6523e |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a251f6786081908eaaed6190695322 |
completed | Feb. 28, 2026, 2:24 a.m. |
Created at: Feb. 28, 2026, 2:02 a.m.