Triple
T10281179
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dominic Toretto |
E241103
|
entity |
| Predicate | alias |
P39
|
FINISHED |
| Object |
Dom
Dom is the street-racing, family-obsessed antihero and central protagonist of the Fast & Furious film franchise, portrayed by Vin Diesel.
|
E852140
|
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: Dom | Statement: [Dominic Toretto, alias, Dom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dom Context triple: [Dominic Toretto, alias, Dom]
-
A.
Dom
Dom is one of the highest and most prominent mountains in the Swiss Alps, renowned for its imposing pyramid shape and challenging climbing routes.
-
B.
Dom
Dom is a Portuguese honorific title traditionally used for nobility, royalty, and certain high-ranking religious figures.
-
C.
Dom
Dom are a traditionally itinerant ethnic group found across the Middle East, North Africa, and parts of South Asia, known for distinct languages, crafts, and musical traditions.
-
D.
Don
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
E.
Don
Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
- 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: Dom Triple: [Dominic Toretto, alias, Dom]
Generated description
Dom is the street-racing, family-obsessed antihero and central protagonist of the Fast & Furious film franchise, portrayed by Vin Diesel.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dom Target entity description: Dom is the street-racing, family-obsessed antihero and central protagonist of the Fast & Furious film franchise, portrayed by Vin Diesel.
-
A.
Dom
Dom is one of the highest and most prominent mountains in the Swiss Alps, renowned for its imposing pyramid shape and challenging climbing routes.
-
B.
Dom
Dom is a Portuguese honorific title traditionally used for nobility, royalty, and certain high-ranking religious figures.
-
C.
Dom
Dom are a traditionally itinerant ethnic group found across the Middle East, North Africa, and parts of South Asia, known for distinct languages, crafts, and musical traditions.
-
D.
Don
Don is a masculine given name, often a short form of Donald, used in English-speaking countries.
-
E.
Don
Don is a classic 1978 Bollywood action-thriller film, starring Amitabh Bachchan in a dual role, that became iconic for its stylish crime narrative, memorable music, and enduring cultural impact.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2a177b48190aab7d7857f5bba7b |
completed | April 7, 2026, 9:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d6f8352a108190b3692a2de3cb4dea |
completed | April 9, 2026, 12:52 a.m. |
| NEDg | Description generation | batch_69d6fcad625881909304201c1ebb3bcb |
completed | April 9, 2026, 1:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d6fd84cd708190816d94417294b52a |
completed | April 9, 2026, 1:14 a.m. |
Created at: April 6, 2026, 11:39 a.m.