Triple
T10257545
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Têt River |
E240510
|
entity |
| Predicate | hasMouthNear |
P350
|
FINISHED |
| Object |
Saint-Cyprien
Saint-Cyprien is a coastal commune in southern France known for its Mediterranean beaches and marina.
|
E854127
|
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: Saint-Cyprien | Statement: [Têt River, hasMouthNear, Saint-Cyprien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Cyprien Context triple: [Têt River, hasMouthNear, Saint-Cyprien]
-
A.
Sainte-Pétronille
Sainte-Pétronille is a small, picturesque municipality located at the western tip of Île d’Orléans in Quebec, Canada, known for its historic charm and scenic views of the St. Lawrence River.
-
B.
Saint-Cyriens
Saint-Cyriens are the officer cadets and alumni of France’s prestigious École spéciale militaire de Saint-Cyr, renowned as the country’s foremost military academy.
-
C.
Tarascon
Tarascon is a historic town in southern France, known for its medieval castle and Provençal heritage along the lower Rhône Valley.
-
D.
Melissant
Melissant is a small village in the Dutch province of South Holland, located on the island of Goeree-Overflakkee.
-
E.
Souillac
Souillac is a picturesque town in southwestern France known for its historic architecture and scenic setting along the Dordogne River.
- 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: Saint-Cyprien Triple: [Têt River, hasMouthNear, Saint-Cyprien]
Generated description
Saint-Cyprien is a coastal commune in southern France known for its Mediterranean beaches and marina.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Saint-Cyprien Target entity description: Saint-Cyprien is a coastal commune in southern France known for its Mediterranean beaches and marina.
-
A.
Sainte-Pétronille
Sainte-Pétronille is a small, picturesque municipality located at the western tip of Île d’Orléans in Quebec, Canada, known for its historic charm and scenic views of the St. Lawrence River.
-
B.
Saint-Cyriens
Saint-Cyriens are the officer cadets and alumni of France’s prestigious École spéciale militaire de Saint-Cyr, renowned as the country’s foremost military academy.
-
C.
Tarascon
Tarascon is a historic town in southern France, known for its medieval castle and Provençal heritage along the lower Rhône Valley.
-
D.
Melissant
Melissant is a small village in the Dutch province of South Holland, located on the island of Goeree-Overflakkee.
-
E.
Souillac
Souillac is a picturesque town in southwestern France known for its historic architecture and scenic setting along the Dordogne River.
- 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_69d381a7e198819090280d5ab885d59e |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d24de4588190b68fb3daa36dbd7d |
completed | April 7, 2026, 9:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f7e153b0819084708b6f7127cdea |
completed | April 9, 2026, 12:50 a.m. |
| NEDg | Description generation | batch_69d6fcab0bfc8190b47bc165ef3eb15d |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d70fc3b15081908d1b67a7094c6210 |
completed | April 9, 2026, 2:32 a.m. |
Created at: April 6, 2026, 11:31 a.m.