Triple
T18781253
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La luna e i falò |
E459261
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Santa
Santa is a character in Cesare Pavese’s novel "La luna e i falò," representing the rural, often harsh realities of life in the Piedmont countryside.
|
E1343529
|
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: Santa | Statement: [La luna e i falò, character, Santa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Context triple: [La luna e i falò, character, Santa]
-
A.
Santa
Santa is another name for the Dongxiang language, a Mongolic language spoken primarily by the Dongxiang ethnic group in Gansu Province, China.
-
B.
Santa
Santa is a small city in Egypt’s Gharbia Governorate, located in the Nile Delta region and known primarily as a local agricultural and market center.
-
C.
Santa Claus
Santa Claus is a legendary, gift-giving figure in Western culture typically depicted as a jolly, bearded man in a red suit who delivers presents to children on Christmas Eve.
-
D.
St. Niklaus
St. Niklaus is a locality within the Swiss municipality of Feldbrunnen-St. Niklaus in the canton of Solothurn.
-
E.
Drosselmeyer
Drosselmeyer is an American Thoroughbred racehorse best known for winning the 2010 Belmont Stakes and the 2011 Breeders’ Cup Classic.
- 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: Santa Triple: [La luna e i falò, character, Santa]
Generated description
Santa is a character in Cesare Pavese’s novel "La luna e i falò," representing the rural, often harsh realities of life in the Piedmont countryside.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Santa Target entity description: Santa is a character in Cesare Pavese’s novel "La luna e i falò," representing the rural, often harsh realities of life in the Piedmont countryside.
-
A.
Santa
Santa is another name for the Dongxiang language, a Mongolic language spoken primarily by the Dongxiang ethnic group in Gansu Province, China.
-
B.
Santa
Santa is a small city in Egypt’s Gharbia Governorate, located in the Nile Delta region and known primarily as a local agricultural and market center.
-
C.
Santa Claus
Santa Claus is a legendary, gift-giving figure in Western culture typically depicted as a jolly, bearded man in a red suit who delivers presents to children on Christmas Eve.
-
D.
St. Niklaus
St. Niklaus is a locality within the Swiss municipality of Feldbrunnen-St. Niklaus in the canton of Solothurn.
-
E.
Drosselmeyer
Drosselmeyer is an American Thoroughbred racehorse best known for winning the 2010 Belmont Stakes and the 2011 Breeders’ Cup Classic.
- 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e5933ee89481908b647802961e4519 |
completed | April 20, 2026, 2:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0547172c4c81909fc7370aa124c2e1 |
completed | May 14, 2026, 3:52 a.m. |
| NEDg | Description generation | batch_6a054a54df1c8190981387ca09193459 |
completed | May 14, 2026, 4:06 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a054b1e79588190b5e50215cecb8029 |
completed | May 14, 2026, 4:10 a.m. |
Created at: April 10, 2026, 11:52 a.m.