Triple
T3853493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Capcir |
E85354
|
entity |
| Predicate | borders |
P224
|
FINISHED |
| Object | Cerdagne |
E104714
|
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: Cerdagne | Statement: [Capcir, borders, Cerdagne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cerdagne Context triple: [Capcir, borders, Cerdagne]
-
A.
Marvejols
Marvejols is a historic town in southern France’s Lozère department, known for its medieval heritage and location near the Aubrac and Margeride regions.
-
B.
Céret
Céret is a historic town in southern France near the Spanish border, renowned for its modern art museum and its association with early 20th-century artists like Picasso and Braque.
-
C.
Vallespir
chosen
Vallespir is a historic Catalan-influenced valley region in the eastern Pyrenees of southern France, known for its spa towns, traditional festivals, and scenic landscapes along the Tech River.
-
D.
Rivesaltes
Rivesaltes is a commune in southern France’s Pyrénées-Orientales department, known for its wine production and historical internment camp.
-
E.
Eygues
Eygues is a river in southeastern France that flows through the Drôme department before joining the larger Rhône basin.
- 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_69aed936de1c81908f91bed80f70abb2 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeec0438308190865ff74bee5a1cf2 |
completed | March 9, 2026, 3:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5627ebbc48190914b663bab5e2a82 |
completed | March 14, 2026, 1:28 p.m. |
Created at: March 9, 2026, 3:19 p.m.