Triple
T16478742
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blessagno |
E400258
|
entity |
| Predicate | sharesBorderWith |
P224
|
FINISHED |
| Object | Laino |
E400259
|
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: Laino | Statement: [Blessagno, sharesBorderWith, Laino]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laino Context triple: [Blessagno, sharesBorderWith, Laino]
-
A.
Laino
chosen
Laino is a small Italian municipality located in the Valle d’Intelvi area of the Lombardy region, near Lake Como.
-
B.
Eligh
Eligh is an American underground hip hop artist and producer best known as a member of the Living Legends collective and for his prolific solo and collaborative work.
-
C.
Lojay
Lojay is a Nigerian singer and songwriter known for his Afro-fusion sound and hit collaborations in contemporary Afrobeats.
-
D.
Josue
Josue is a given name, commonly used in Spanish and Portuguese, that corresponds to the biblical name Joshua.
-
E.
Tainy
Tainy is a Puerto Rican record producer and songwriter renowned for shaping modern reggaeton and Latin urban music through hits with artists like Bad Bunny, J Balvin, and Daddy Yankee.
- 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_69d883813098819084f5409539723b59 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32e01230881908b2147a25f78b7f4 |
completed | April 18, 2026, 7:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a004f60ea8881908f073a28c407a1f4 |
completed | May 10, 2026, 9:26 a.m. |
Created at: April 10, 2026, 5:13 a.m.