Triple
T26650661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sandpiper Air |
E669040
|
entity |
| Predicate | fictionalRouteRegion |
P90813
|
FINISHED |
| Object | New England |
—
|
NE NERFINISHED |
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: New England | Statement: [Sandpiper Air, fictionalRouteRegion, New England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalRouteRegion Context triple: [Sandpiper Air, fictionalRouteRegion, New England]
-
A.
routeRegion
Indicates that a route is located within, passes through, or is associated with a particular geographic region.
-
B.
locatedOnFictionalRoute
chosen
Indicates that something is situated along or associated with a route that exists only within a fictional or imaginary setting.
-
C.
fictionalGeographicRegion
Indicates that a geographic region exists only in fiction or imagination rather than in the real world.
-
D.
fictionalSettingRegion
Indicates that a fictional setting is located within or associated with a specific geographic or administrative region.
-
E.
belongsToFictionalRegion
Indicates that an entity is located within, associated with, or under the jurisdiction of a fictional or imaginary geographic region.
- 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_69ee9d00eb5481908d6c6d0ada2f0c9a |
completed | April 26, 2026, 11:17 p.m. |
| NER | Named-entity recognition | batch_69f68805b4848190b75da14996d52a38 |
completed | May 2, 2026, 11:25 p.m. |
| PD | Predicate disambiguation | batch_69f68609c0b08190a8e1238a4d97c270 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 27, 2026, 2:32 a.m.