Triple
T4958330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanaro |
E111341
|
entity |
| Predicate | passesThrough |
P225
|
FINISHED |
| Object |
Ormea
Ormea is a small mountain town in the Piedmont region of northwestern Italy, located in the Ligurian Alps near the source of the Tanaro River.
|
E483102
|
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: Ormea | Statement: [Tanaro, passesThrough, Ormea]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ormea Context triple: [Tanaro, passesThrough, Ormea]
-
A.
Bigorre
Bigorre is a historic cultural region in southwestern France, centered around the foothills of the Pyrenees and now largely within the modern Occitanie administrative region.
-
B.
Miravalle
Miravalle is a neighborhood located within the Benito Juárez borough of Mexico City, known for its residential character and urban amenities.
-
C.
Murino
Murino is a rapidly growing suburban town on the outskirts of Saint Petersburg in northwestern Russia.
-
D.
Mauguio
Mauguio is a commune in southern France near Montpellier, known for its proximity to the Mediterranean coast and its role as a local economic and transport hub.
-
E.
Arogno
Arogno is a small municipality in the canton of Ticino in southern Switzerland, located near Lake Lugano and the Italian border.
- 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: Ormea Triple: [Tanaro, passesThrough, Ormea]
Generated description
Ormea is a small mountain town in the Piedmont region of northwestern Italy, located in the Ligurian Alps near the source of the Tanaro River.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Ormea Target entity description: Ormea is a small mountain town in the Piedmont region of northwestern Italy, located in the Ligurian Alps near the source of the Tanaro River.
-
A.
Bigorre
Bigorre is a historic cultural region in southwestern France, centered around the foothills of the Pyrenees and now largely within the modern Occitanie administrative region.
-
B.
Miravalle
Miravalle is a neighborhood located within the Benito Juárez borough of Mexico City, known for its residential character and urban amenities.
-
C.
Murino
Murino is a rapidly growing suburban town on the outskirts of Saint Petersburg in northwestern Russia.
-
D.
Mauguio
Mauguio is a commune in southern France near Montpellier, known for its proximity to the Mediterranean coast and its role as a local economic and transport hub.
-
E.
Arogno
Arogno is a small municipality in the canton of Ticino in southern Switzerland, located near Lake Lugano and the Italian border.
- 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_69bd4418390c8190b7e9766a2512ce55 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd71d834c0819087f3faafdc9b4228 |
completed | March 20, 2026, 4:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be81e144a08190b66bf07e09b6ff55 |
completed | March 21, 2026, 11:32 a.m. |
| NEDg | Description generation | batch_69be83b10e048190889289ac2ca9f07f |
completed | March 21, 2026, 11:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69be843e2e50819099b2b73498c7c16e |
completed | March 21, 2026, 11:42 a.m. |
Created at: March 20, 2026, 1:32 p.m.