Triple
T15676150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Count of Lavagna |
E377449
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Lavagna |
E377450
|
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: Lavagna | Statement: [Count of Lavagna, locatedIn, Lavagna]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lavagna Context triple: [Count of Lavagna, locatedIn, Lavagna]
-
A.
Lavagna
chosen
Lavagna is a historic coastal town in the Liguria region of northwestern Italy, known for its medieval heritage and traditional slate production.
-
B.
Tahta
Tahta is a city in Upper Egypt located within the Sohag Governorate, known as a regional center for agriculture and local trade along the Nile.
-
C.
Tábua
Tábua is a municipality in central Portugal known for its rural landscapes, traditional villages, and location between the Mondego and Alva rivers.
-
D.
Tablón
Tablón is a notable summit of the El Altar volcanic complex in the Ecuadorian Andes, known for its rugged terrain and high-altitude Andean landscapes.
-
E.
Gessate
Gessate is a municipality in the Metropolitan City of Milan, Lombardy, Italy, known for serving as a terminus of Milan Metro Line 2.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2e10a4819097eba1ea31e36ac2 |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6edd85148190b6d5c3981204dd77 |
completed | May 9, 2026, 5:29 p.m. |
Created at: April 10, 2026, 4:16 a.m.