Triple
T521752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Garonne |
E10830
|
entity |
| Predicate | cityOnRiver |
P165
|
FINISHED |
| Object | Marmande |
E83980
|
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: Marmande | Statement: [Garonne, cityOnRiver, Marmande]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marmande Context triple: [Garonne, cityOnRiver, Marmande]
-
A.
Marmande
chosen
Marmande is a town in southwestern France known for its agricultural production, particularly tomatoes, and its location in the Garonne River valley.
-
B.
Bourgueil
Bourgueil is a Loire Valley wine appellation in France renowned for its red wines, particularly those made predominantly from Cabernet Franc.
-
C.
Boncourt
Boncourt is a locality known for its historic Château de Boncourt, reflecting its cultural and architectural heritage.
-
D.
Anjou
Anjou is a historic region in western France that was once a powerful medieval county and later a duchy, playing a central role in the Angevin Empire and European dynastic politics.
-
E.
Dijon
Dijon is a historic city in eastern France renowned for its rich architectural heritage, former status as the capital of the Duchy of Burgundy, and its famous mustard.
- 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_69a2e84b16c4819088d284c47c3a7968 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2f1b372408190b3918fec45444674 |
completed | Feb. 28, 2026, 1:46 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a7a3a260888190b89e90c1da061733 |
completed | March 4, 2026, 3:14 a.m. |
Created at: Feb. 28, 2026, 1:12 p.m.