Triple
T13458228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ferdinand Sarrien |
E311289
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Sarrien
Sarrien is a French surname most notably borne by Ferdinand Sarrien, a politician who served as Prime Minister of France in the early 20th century.
|
E1041298
|
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: Sarrien | Statement: [Ferdinand Sarrien, familyName, Sarrien]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sarrien Context triple: [Ferdinand Sarrien, familyName, Sarrien]
-
A.
Saravena
Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
-
B.
Sardoal
Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
-
C.
Sierroz
Sierroz is a river in eastern France that serves as one of the tributaries feeding into Lac du Bourget.
-
D.
Sareyn
Sareyn is a small Iranian town renowned for its natural hot springs and status as a popular health and tourism destination.
-
E.
Navarrenx
Navarrenx is a historic fortified town in southwestern France, known for its well-preserved ramparts and strategic position in the Béarn region.
- 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: Sarrien Triple: [Ferdinand Sarrien, familyName, Sarrien]
Generated description
Sarrien is a French surname most notably borne by Ferdinand Sarrien, a politician who served as Prime Minister of France in the early 20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sarrien Target entity description: Sarrien is a French surname most notably borne by Ferdinand Sarrien, a politician who served as Prime Minister of France in the early 20th century.
-
A.
Saravena
Saravena is a Colombian town and municipality located in the northeastern oil-producing and conflict-affected region near the border with Venezuela.
-
B.
Sardoal
Sardoal is a small Portuguese municipality known for its historic village center and traditional religious and cultural festivities, located in the Centro Region of Portugal.
-
C.
Sierroz
Sierroz is a river in eastern France that serves as one of the tributaries feeding into Lac du Bourget.
-
D.
Sareyn
Sareyn is a small Iranian town renowned for its natural hot springs and status as a popular health and tourism destination.
-
E.
Navarrenx
Navarrenx is a historic fortified town in southwestern France, known for its well-preserved ramparts and strategic position in the Béarn region.
- 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_69d806a938b8819097ec43a2229fc7f9 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69dbaf0a75008190a508060c85f73604 |
completed | April 12, 2026, 2:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f739a001d08190ae5664c6670540e7 |
completed | May 3, 2026, 12:03 p.m. |
| NEDg | Description generation | batch_69f73b3074bc819081e30b082857c33e |
completed | May 3, 2026, 12:10 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f73ee5839881908ce75c57f1942b57 |
completed | May 3, 2026, 12:26 p.m. |
Created at: April 9, 2026, 9:41 p.m.