Triple
T2391206
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lope National Park |
E48946
|
entity |
| Predicate | nearestCity |
P350
|
FINISHED |
| Object | Booué |
E280665
|
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: Booué | Statement: [Lope National Park, nearestCity, Booué]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Booué Context triple: [Lope National Park, nearestCity, Booué]
-
A.
Booué
chosen
Booué is a small town in central Gabon situated along the Ogooué River, known as a local transport and trading hub in the region.
-
B.
Bourdigny
Bourdigny is a small village within the municipality of Satigny in the canton of Geneva, Switzerland.
-
C.
Éveux
Éveux is a small commune in eastern France’s Rhône department, known for hosting Le Corbusier’s modernist monastery, the Couvent Sainte-Marie de La Tourette.
-
D.
Sauvy
Sauvy is a French surname most notably borne by Alfred Sauvy, a prominent demographer, sociologist, and economist.
-
E.
Buzet
Buzet is a French wine appellation in the Lot-et-Garonne department known for its red, white, and rosé wines primarily based on Bordeaux grape varieties.
- 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_69a88aa5f63081908d07fd302029fcbd |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc87457388190822d5506327db8f2 |
completed | March 7, 2026, 6:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af98a342508190b30766327f298bf9 |
completed | March 10, 2026, 4:05 a.m. |
Created at: March 4, 2026, 7:57 p.m.