Triple
T13936352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Arthur (2004 film) |
E335130
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object |
Bors
Bors is a gruff, battle-hardened knight and loyal companion of Arthur in the 2004 film "King Arthur," often providing comic relief amid the film’s gritty realism.
|
E1069538
|
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: Bors | Statement: [King Arthur (2004 film), character, Bors]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bors Context triple: [King Arthur (2004 film), character, Bors]
-
A.
Bor
Bor is a town in Nizhny Novgorod Oblast, Russia, located on the left bank of the Volga River opposite the city of Nizhny Novgorod and known for its industrial and river transport significance.
-
B.
Bor
Bor is a major town in South Sudan’s Jonglei State, situated on the White Nile and serving as an important regional administrative and transport hub.
-
C.
Bor
Bor is a London Underground station serving the Borough area of Southwark in central London.
-
D.
Bor
Bor is a small town in the Plzeň Region of the Czech Republic, known for its historic architecture and surrounding rural landscape.
-
E.
Borsad
Borsad is a town in the Indian state of Gujarat known for its agricultural markets and role as a local commercial center.
- 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: Bors Triple: [King Arthur (2004 film), character, Bors]
Generated description
Bors is a gruff, battle-hardened knight and loyal companion of Arthur in the 2004 film "King Arthur," often providing comic relief amid the film’s gritty realism.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bors Target entity description: Bors is a gruff, battle-hardened knight and loyal companion of Arthur in the 2004 film "King Arthur," often providing comic relief amid the film’s gritty realism.
-
A.
Bor
Bor is a town in Nizhny Novgorod Oblast, Russia, located on the left bank of the Volga River opposite the city of Nizhny Novgorod and known for its industrial and river transport significance.
-
B.
Bor
Bor is a major town in South Sudan’s Jonglei State, situated on the White Nile and serving as an important regional administrative and transport hub.
-
C.
Bor
Bor is a London Underground station serving the Borough area of Southwark in central London.
-
D.
Bor
Bor is a small town in the Plzeň Region of the Czech Republic, known for its historic architecture and surrounding rural landscape.
-
E.
Borsad
Borsad is a town in the Indian state of Gujarat known for its agricultural markets and role as a local commercial center.
- 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_69d81c5f739081908bc05b2461f54828 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2cf42878819085146670d7b92605 |
completed | April 14, 2026, 12:03 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7ce880a98819086ae25d3408bc723 |
completed | May 3, 2026, 10:39 p.m. |
| NEDg | Description generation | batch_69f7cf24c9d88190b6e93859cb3659ef |
completed | May 3, 2026, 10:41 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7cfa34a448190affb5b86efc37cf4 |
completed | May 3, 2026, 10:43 p.m. |
Created at: April 9, 2026, 10:17 p.m.