Triple
T2460699
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amber Fort |
E54526
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Amer |
E152261
|
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: Amer | Statement: [Amber Fort, locatedIn, Amer]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Amer Context triple: [Amber Fort, locatedIn, Amer]
-
A.
Amer
chosen
Amer is a common Arabic surname borne by various notable individuals across the Middle East and North Africa.
-
B.
Amery
Amery is an English surname most notably associated with a British political family, including Conservative politician Julian Amery.
-
C.
Amerika
Amerika is a novel by Franz Kafka that follows a young European immigrant’s surreal and often absurd experiences in the United States.
-
D.
Beni-Amer
The Beni-Amer are a pastoralist ethnic group of mixed Beja and Tigre heritage living primarily in eastern Sudan and western Eritrea.
-
E.
America
America is the landmass in the Western Hemisphere comprising the continents of North and South America, widely recognized for its vast geographic, cultural, and political diversity.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd10ba66481909580e994b22fd406 |
completed | March 7, 2026, 7:17 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0d2b2748190b12611863d8bf4ad |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:44 p.m.