Triple
T2122319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seine-et-Marne |
E43951
|
entity |
| Predicate | prefecture |
P7509
|
FINISHED |
| Object | Melun |
E74146
|
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: Melun | Statement: [Seine-et-Marne, prefecture, Melun]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Melun Context triple: [Seine-et-Marne, prefecture, Melun]
-
A.
Melun
chosen
Melun is a historic commune in the Île-de-France region of north-central France, known as a regional administrative center and former royal town southeast of Paris.
-
B.
Blois
Blois is a historic city in central France known for its Renaissance château, picturesque setting on the Loire River, and rich royal heritage.
-
C.
Poissy
Poissy is a commune in the western suburbs of Paris, France, known for hosting Le Corbusier’s iconic modernist Villa Savoye.
-
D.
Tournus
Tournus is a historic town in eastern France’s Burgundy region, known for its Romanesque abbey and riverside setting along the Saône.
-
E.
Creil
Creil is a commuter town in northern France’s Oise department, known as a regional rail hub connecting Paris with Picardy via major train and RER lines.
- 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_69a88717cfe48190b7ecdd68c824848a |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abbb51e8088190a1aeafee4e8dff63 |
completed | March 7, 2026, 5:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b235511e848190897493ab54d2f198 |
completed | March 12, 2026, 3:38 a.m. |
Created at: March 4, 2026, 7:44 p.m.