Triple
T13991803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kosrae International Airport |
E336595
|
entity |
| Predicate | nearbySettlement |
P350
|
FINISHED |
| Object | Tofol |
E336593
|
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: Tofol | Statement: [Kosrae International Airport, nearbySettlement, Tofol]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tofol Context triple: [Kosrae International Airport, nearbySettlement, Tofol]
-
A.
Tofol
chosen
Tofol is the administrative center and main town of Kosrae State in the Federated States of Micronesia.
-
B.
Tocho
Tocho is the common nickname for the Tokyo Metropolitan Government Building, a prominent skyscraper complex in Shinjuku that houses Tokyo’s metropolitan administration and offers popular observation decks.
-
C.
Tost
Tost is a town in present-day Toszek, Poland, historically part of Upper Silesia.
-
D.
Tororo
Tororo is a town in eastern Uganda known as an important commercial and transport hub near the Kenyan border.
-
E.
Quorn
Quorn is a village in Leicestershire, England, known for its historic charm and proximity to the River Soar and the Great Central Railway.
- 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_69d81c639e808190a0e4b4f3d31c6a59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2eb3b5d881909f15a1e08bb202f3 |
completed | April 14, 2026, 12:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcb652305c81908ea097d4f36a05c0 |
completed | May 7, 2026, 3:57 p.m. |
Created at: April 9, 2026, 10:19 p.m.