Triple
T3691811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philomena |
E78359
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object |
Valerio Bonelli
Valerio Bonelli is a film editor known for his work on acclaimed movies such as "Philomena."
|
E380298
|
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: Valerio Bonelli | Statement: [Philomena, editedBy, Valerio Bonelli]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valerio Bonelli Context triple: [Philomena, editedBy, Valerio Bonelli]
-
A.
Riccardo Mazzucchelli
Riccardo Mazzucchelli was an Italian businessman and entrepreneur known for his brief high-profile marriage to socialite and businesswoman Ivana Trump.
-
B.
Rossano Rubicondi
Rossano Rubicondi was an Italian actor, model, and television personality best known internationally for his high-profile marriage to Ivana Trump.
-
C.
Rafael Sabatini
Rafael Sabatini was an Italian-English author best known for his swashbuckling historical adventure novels such as "Scaramouche" and "Captain Blood."
-
D.
Agenore Incrocci
Agenore Incrocci was an Italian screenwriter, best known as part of the celebrated writing duo Age & Scarpelli, who helped shape classic Italian cinema and comedy.
-
E.
Ettore de Rossi
Ettore de Rossi was an Italian general who commanded forces of the Italian Army in Russia (ARMIR) during World War II.
- 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: Valerio Bonelli Triple: [Philomena, editedBy, Valerio Bonelli]
Generated description
Valerio Bonelli is a film editor known for his work on acclaimed movies such as "Philomena."
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Valerio Bonelli Target entity description: Valerio Bonelli is a film editor known for his work on acclaimed movies such as "Philomena."
-
A.
Riccardo Mazzucchelli
Riccardo Mazzucchelli was an Italian businessman and entrepreneur known for his brief high-profile marriage to socialite and businesswoman Ivana Trump.
-
B.
Rossano Rubicondi
Rossano Rubicondi was an Italian actor, model, and television personality best known internationally for his high-profile marriage to Ivana Trump.
-
C.
Rafael Sabatini
Rafael Sabatini was an Italian-English author best known for his swashbuckling historical adventure novels such as "Scaramouche" and "Captain Blood."
-
D.
Agenore Incrocci
Agenore Incrocci was an Italian screenwriter, best known as part of the celebrated writing duo Age & Scarpelli, who helped shape classic Italian cinema and comedy.
-
E.
Ettore de Rossi
Ettore de Rossi was an Italian general who commanded forces of the Italian Army in Russia (ARMIR) during World War II.
- 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_69ad85e285a081908f8cbfa9e2ed9b75 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc4e783a88190b2837a68b8723a25 |
completed | March 8, 2026, 6:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b4c3c9e9c08190bd97642ccf39b172 |
completed | March 14, 2026, 2:11 a.m. |
| NEDg | Description generation | batch_69b4c78bca688190bb06f64827285790 |
completed | March 14, 2026, 2:27 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b4c7f33dec8190b71ea08cb1d34c32 |
completed | March 14, 2026, 2:29 a.m. |
Created at: March 8, 2026, 3:26 p.m.