Triple
T6980639
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terra Nova Bay |
E161833
|
entity |
| Predicate | nearbyResearchStationSeasonality |
P45261
|
FINISHED |
| Object | summer-only station |
—
|
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: summer-only station | Statement: [Terra Nova Bay, nearbyResearchStationSeasonality, summer-only station]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyResearchStationSeasonality Context triple: [Terra Nova Bay, nearbyResearchStationSeasonality, summer-only station]
-
A.
hasSeasonalResearchPresence
chosen
Indicates that an entity conducts research activities in a location only during specific seasons or times of the year.
-
B.
containsResearchStation
Indicates that one entity geographically includes or hosts a research station within its boundaries.
-
C.
nearestResearchStation
Indicates that one research station is the closest in distance to a given location or entity compared to all other research stations.
-
D.
researchStationStatus
Indicates the current operational or functional state of a research station within a given context or system.
-
E.
hasMeteorologicalStation
Indicates that one entity possesses, hosts, or is equipped with a meteorological station used for observing and recording weather-related data.
- 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_69c68855dc0481909b4c7e9e9ed273db |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db6c1efc8190ab1575ae2ce726db |
completed | March 27, 2026, 7:33 p.m. |
| PD | Predicate disambiguation | batch_69c6d7c262508190a7708b3d9cf23d7c |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:31 p.m.