Triple
T18252706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vas Blackwood |
E437135
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object |
Vas
Vas is the given name of British actor Vas Blackwood, known for his roles in films like "Lock, Stock and Two Smoking Barrels" and various UK television series.
|
E1314667
|
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: Vas | Statement: [Vas Blackwood, givenName, Vas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vas Context triple: [Vas Blackwood, givenName, Vas]
-
A.
Tunge
Tunge is a small locality in western Sweden situated within Lilla Edet Municipality in Västra Götaland County.
-
B.
Vasagatan
Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
-
C.
Vaslui
Vaslui is a city in eastern Romania, serving as the capital of Vaslui County and known for its historical significance in the Moldavia region.
-
D.
Avalа
Avala is a prominent mountain near Belgrade in central Serbia, known for its scenic views, historical monuments, and the Avala TV Tower.
-
E.
Vire
Vire is a historic town in northwestern France known for its medieval heritage and role as an administrative center in the Calvados department of Normandy.
- 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: Vas Triple: [Vas Blackwood, givenName, Vas]
Generated description
Vas is the given name of British actor Vas Blackwood, known for his roles in films like "Lock, Stock and Two Smoking Barrels" and various UK television series.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vas Target entity description: Vas is the given name of British actor Vas Blackwood, known for his roles in films like "Lock, Stock and Two Smoking Barrels" and various UK television series.
-
A.
Tunge
Tunge is a small locality in western Sweden situated within Lilla Edet Municipality in Västra Götaland County.
-
B.
Vasagatan
Vasagatan is a major central street in Stockholm, Sweden, known for its busy traffic, shops, and proximity to Stockholm Central Station.
-
C.
Vaslui
Vaslui is a city in eastern Romania, serving as the capital of Vaslui County and known for its historical significance in the Moldavia region.
-
D.
Avalа
Avala is a prominent mountain near Belgrade in central Serbia, known for its scenic views, historical monuments, and the Avala TV Tower.
-
E.
Vire
Vire is a historic town in northwestern France known for its medieval heritage and role as an administrative center in the Calvados department of Normandy.
- 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_69d8b91104e08190a8241f7d260a5162 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd81ea3481909d96b5399f7a32b3 |
completed | April 19, 2026, 4:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a03ac77ae948190bddece9dbc21fd47 |
completed | May 12, 2026, 10:40 p.m. |
| NEDg | Description generation | batch_6a03ad91e258819093a80d78da6d6995 |
completed | May 12, 2026, 10:45 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a03b032ab20819098391050267af59b |
completed | May 12, 2026, 10:56 p.m. |
Created at: April 10, 2026, 10:33 a.m.