Triple
T6665344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nippes Department |
E151586
|
entity |
| Predicate | hasSettlement |
P1068
|
FINISHED |
| Object | Miragoâne |
E608941
|
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: Miragoâne | Statement: [Nippes Department, hasSettlement, Miragoâne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miragoâne Context triple: [Nippes Department, hasSettlement, Miragoâne]
-
A.
Miragoâne
chosen
Miragoâne is a coastal city in southwestern Haiti that serves as an important regional port and administrative center.
-
B.
Peloursin
Peloursin is a relatively obscure French red wine grape variety historically grown in the Rhône and Isère regions and best known today as a parent of Petite Sirah (Durif).
-
C.
Tatihou
Tatihou is a small French island off the coast of Normandy known for its historic Vauban fortifications, maritime museum, and rich coastal birdlife.
-
D.
Burdigala
Burdigala was the ancient Roman-era city in Gaul that later became modern-day Bordeaux, an important commercial and cultural center.
-
E.
Marignane
Marignane is a commune in southern France near Marseille, known for hosting Marseille Provence Airport and its proximity to the Mediterranean coast.
- 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_69c687f71fc081909dbd45d6377f6045 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6b09d97648190a254cabc0ffcb0dc |
completed | March 27, 2026, 4:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c700755874819083cd0facebd7aa3d |
completed | March 27, 2026, 10:11 p.m. |
Created at: March 27, 2026, 2:02 p.m.