Triple
T4809813
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nabiac |
E107039
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Forster |
E102824
|
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: Forster | Statement: [Nabiac, locatedNear, Forster]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Forster Context triple: [Nabiac, locatedNear, Forster]
-
A.
Forster
chosen
Forster is a coastal town in New South Wales, Australia, known for its beaches, fishing, and holiday tourism.
-
B.
Anne Forster
Anne Forster was the wife of the Irish philosopher and Anglican bishop George Berkeley, known primarily through her marriage into his prominent intellectual and clerical household.
-
C.
June Forster
June Forster is known as the wife of American actor Robert Forster.
-
D.
Albert Forster
Albert Forster was a prominent Nazi official who served as Gauleiter and later governor in occupied Polish territories during the Second World War, overseeing brutal Germanization and repression policies.
-
E.
Fowler
Fowler is a surname of English origin borne by numerous notable individuals across fields such as engineering, politics, sports, and the arts.
- 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_69bd43f779448190b92885cb70abb6c2 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6c6c70a88190aa287fc78716c225 |
completed | March 20, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be4daa52ec8190a3243313b18a4f3d |
completed | March 21, 2026, 7:50 a.m. |
Created at: March 20, 2026, 1:23 p.m.