Triple
T11399031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lino Lacedelli |
E270057
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Lacedelli |
E270057
|
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: Lacedelli | Statement: [Lino Lacedelli, familyName, Lacedelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lacedelli Context triple: [Lino Lacedelli, familyName, Lacedelli]
-
A.
Lacedelli
chosen
Lacedelli is an Italian surname most notably associated with Lino Lacedelli, one of the first climbers to reach the summit of K2.
-
B.
Lumarzo
Lumarzo is a small municipality in the Liguria region of northwestern Italy, located in the hilly inland area near Genoa.
-
C.
Lazzara
Lazzara is the birth surname of acclaimed American actress and singer Bernadette Peters.
-
D.
Caselotti
Caselotti is an Italian surname most notably associated with Adriana Caselotti, the original voice of Snow White in Disney’s 1937 animated film.
-
E.
Molinaro
Molinaro is an Italian occupational surname, historically associated with millers and derived from the same root as "Molinero."
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d8001adc188190ae45227856156412 |
completed | April 9, 2026, 7:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58cf75ec08190a571e5178bcde274 |
completed | April 20, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:34 p.m.