Triple
T6901789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northern Haiti |
E159511
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object |
Sainte-Suzanne
Sainte-Suzanne is a commune in northern Haiti known for its rural character and agricultural activities within the Nord-Est department.
|
E627231
|
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: Sainte-Suzanne | Statement: [Northern Haiti, contains, Sainte-Suzanne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sainte-Suzanne Context triple: [Northern Haiti, contains, Sainte-Suzanne]
-
A.
Souvigny
Souvigny is a historic town in central France known for its important Cluniac priory and medieval religious heritage.
-
B.
Boussy-Saint-Antoine
Boussy-Saint-Antoine is a suburban commune in the Essonne department in the Île-de-France region of northern France.
-
C.
La Verrière
La Verrière is a suburban commune in the Yvelines department of north-central France, located within the Paris metropolitan area.
-
D.
Reyssouze
Reyssouze is a river in eastern France that flows through the Ain department and the town of Bourg-en-Bresse.
-
E.
Chassezac
The Chassezac is a river in southern France known for flowing through the Cévennes region and forming scenic gorges popular for outdoor activities like canoeing and rock climbing.
- 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: Sainte-Suzanne Triple: [Northern Haiti, contains, Sainte-Suzanne]
Generated description
Sainte-Suzanne is a commune in northern Haiti known for its rural character and agricultural activities within the Nord-Est department.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sainte-Suzanne Target entity description: Sainte-Suzanne is a commune in northern Haiti known for its rural character and agricultural activities within the Nord-Est department.
-
A.
Souvigny
Souvigny is a historic town in central France known for its important Cluniac priory and medieval religious heritage.
-
B.
Boussy-Saint-Antoine
Boussy-Saint-Antoine is a suburban commune in the Essonne department in the Île-de-France region of northern France.
-
C.
La Verrière
La Verrière is a suburban commune in the Yvelines department of north-central France, located within the Paris metropolitan area.
-
D.
Reyssouze
Reyssouze is a river in eastern France that flows through the Ain department and the town of Bourg-en-Bresse.
-
E.
Chassezac
The Chassezac is a river in southern France known for flowing through the Cévennes region and forming scenic gorges popular for outdoor activities like canoeing and rock climbing.
- 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_69c6883822e0819091e321526f20ae0a |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6d98749208190842ac075255ca249 |
completed | March 27, 2026, 7:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c748f0dc448190914e38d780644698 |
completed | March 28, 2026, 3:20 a.m. |
| NEDg | Description generation | batch_69c749f7ab5c8190ab823fac27f7484d |
completed | March 28, 2026, 3:24 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c74a6f828c8190bf0cc56227b1a5b2 |
completed | March 28, 2026, 3:26 a.m. |
Created at: March 27, 2026, 2:24 p.m.