Triple
T3297247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Abruzzo |
E69244
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Majella |
E344593
|
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: Majella | Statement: [Abruzzo, contains, Majella]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Majella Context triple: [Abruzzo, contains, Majella]
-
A.
Maiella
chosen
Maiella is a prominent massif in central Italy known for its rugged limestone peaks, deep valleys, and protected landscapes within the Apennine mountain range.
-
B.
Maladeta massif
The Maladeta massif is a prominent mountain group in the central Pyrenees of Spain, known for containing the range’s highest peaks and extensive glaciation.
-
C.
Monte Argentera
Monte Argentera is a prominent mountain peak in the southwestern Alps of Italy, known for its rugged terrain and popularity among climbers and hikers.
-
D.
Monchique
Monchique is a mountainous spa town in southern Portugal known for its lush forests, thermal springs, and panoramic views over the Algarve region.
-
E.
Monte Patria
Monte Patria is a rural municipality and town in Chile’s Coquimbo Region, known for its agricultural production and scenic valleys.
- 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_69ad859e529c8190a404273f53cb487d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb078f3dc8190afb624f62894e48f |
completed | March 8, 2026, 5:23 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b2f3d35c448190a4ca50ae31639e65 |
completed | March 12, 2026, 5:11 p.m. |
Created at: March 8, 2026, 3:10 p.m.