Triple
T3516449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Edward Point |
E74318
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Grytviken |
E73752
|
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: Grytviken | Statement: [King Edward Point, near, Grytviken]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Grytviken Context triple: [King Edward Point, near, Grytviken]
-
A.
Grytviken
chosen
Grytviken is a former whaling station and now-abandoned settlement on the island of South Georgia, notable for its historical role in Antarctic exploration and as the burial place of Ernest Shackleton.
-
B.
Barentsburg
Barentsburg is a Russian mining settlement on the Norwegian archipelago of Svalbard, known for its coal industry and Soviet-era character.
-
C.
Longyearbyen
Longyearbyen is the world’s northernmost permanent settlement and the largest town in the Norwegian Arctic archipelago of Svalbard.
-
D.
Hvalsey
Hvalsey is the best-preserved Norse ruin site in Greenland, known for its stone church and remnants of a medieval farming settlement.
-
E.
Lenakel
Lenakel is an Oceanic language spoken primarily on Tanna Island in Vanuatu.
- 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_69ad85cfb5c881909c9a2edd9d6043cc |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc31c0688190a890621a901f5f5f |
completed | March 8, 2026, 6:13 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b37e7da9c08190ab417b45339513bd |
completed | March 13, 2026, 3:03 a.m. |
Created at: March 8, 2026, 3:19 p.m.