Triple
T7006995
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Hope, Rhode Island |
E162480
|
entity |
| Predicate | indigenousName |
P1435
|
FINISHED |
| Object | Montaup |
E635729
|
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: Montaup | Statement: [Mount Hope, Rhode Island, indigenousName, Montaup]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Montaup Context triple: [Mount Hope, Rhode Island, indigenousName, Montaup]
-
A.
Montaup
chosen
Montaup is an alternate name for Mount Hope, a prominent historic hill and landmark in Rhode Island.
-
B.
Riorges
Riorges is a commune in central France, near Roanne in the Loire department, known for its residential character and local cultural life.
-
C.
La Bresse
La Bresse is a French mountain town in northeastern France known for its ski resort and outdoor activities in the Vosges.
-
D.
Veytaux
Veytaux is a small municipality on the shores of Lake Geneva in the canton of Vaud, Switzerland, known for its scenic setting and proximity to the historic Château de Chillon.
-
E.
Armançon
Armançon is a river in central-eastern France that flows through the Burgundy region before joining the Yonne River.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc35cb848190a839919021efce81 |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7884537708190a35d6988b1fa9b15 |
completed | March 28, 2026, 7:50 a.m. |
Created at: March 27, 2026, 2:33 p.m.