Triple
T3853333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agly |
E85349
|
entity |
| Predicate | flowsNear |
P350
|
FINISHED |
| Object |
Le Barcarès
Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
|
E392501
|
NE FINISHED |
How this triple was built (4 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: Le Barcarès | Statement: [Agly, flowsNear, Le Barcarès]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Le Barcarès Context triple: [Agly, flowsNear, Le Barcarès]
-
A.
Pas de Peyrol
Pas de Peyrol is a high mountain pass in France’s Massif Central, known as the highest road pass in the Cantal department and a key access point to the Puy Mary.
-
B.
Le Lavandou
Le Lavandou is a seaside resort town on the French Riviera in southeastern France, known for its sandy beaches and Mediterranean coastal scenery.
-
C.
La Bérarde
La Bérarde is a small alpine hamlet in the French Alps, known as a base for mountaineering and hiking in the Écrins massif.
-
D.
La Paillade
La Paillade is the traditional nickname of French football club Montpellier HSC, widely used by supporters and media to refer to the team.
-
E.
La Môle
La Môle is a central fictional nobleman and lover in Alexandre Dumas’s historical novel "Queen Margot," set amid the intrigues and violence of 16th-century France.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Le Barcarès Triple: [Agly, flowsNear, Le Barcarès]
Generated description
Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Le Barcarès Target entity description: Le Barcarès is a coastal commune in southern France on the Mediterranean Sea, known for its beaches, marina, and tourism.
-
A.
Pas de Peyrol
Pas de Peyrol is a high mountain pass in France’s Massif Central, known as the highest road pass in the Cantal department and a key access point to the Puy Mary.
-
B.
Le Lavandou
Le Lavandou is a seaside resort town on the French Riviera in southeastern France, known for its sandy beaches and Mediterranean coastal scenery.
-
C.
La Bérarde
La Bérarde is a small alpine hamlet in the French Alps, known as a base for mountaineering and hiking in the Écrins massif.
-
D.
La Paillade
La Paillade is the traditional nickname of French football club Montpellier HSC, widely used by supporters and media to refer to the team.
-
E.
La Môle
La Môle is a central fictional nobleman and lover in Alexandre Dumas’s historical novel "Queen Margot," set amid the intrigues and violence of 16th-century France.
- F. None of above. chosen
Provenance (5 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_69b5041c7250819093b2743afeb6e36c |
completed | March 14, 2026, 6:45 a.m. |
| NEDg | Description generation | batch_69b504c46dcc8190a9775c39e5c734a9 |
completed | March 14, 2026, 6:48 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b505742830819093a861bde17c03c0 |
completed | March 14, 2026, 6:51 a.m. |
Created at: March 9, 2026, 3:19 p.m.