Triple
T15059440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Flood |
E379585
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Tony Flood
Tony Flood is a notable individual recognized for achievements significant enough to be associated with the surname Flood.
|
E1139198
|
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: Tony Flood | Statement: [Flood, hasNotableBearer, Tony Flood]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tony Flood Context triple: [Flood, hasNotableBearer, Tony Flood]
-
A.
Brendan Flood
Brendan Flood is a British businessman best known for his involvement in football club ownership and property development.
-
B.
Tim Fywell
Tim Fywell is a British film and television director known for his work on literary adaptations and period dramas.
-
C.
Keith Fenton
Keith Fenton is the charming yet unfaithful boyfriend whose behavior sparks the romantic mind games at the center of the film "Two Can Play That Game."
-
D.
Brian Frosh
Brian Frosh is an American lawyer and Democratic politician who served as the Attorney General of Maryland from 2015 to 2023.
-
E.
Tony Britton
Tony Britton was a British actor known for his extensive work in film, television, and theatre from the mid-20th century onward.
- 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: Tony Flood Triple: [Flood, hasNotableBearer, Tony Flood]
Generated description
Tony Flood is a notable individual recognized for achievements significant enough to be associated with the surname Flood.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tony Flood Target entity description: Tony Flood is a notable individual recognized for achievements significant enough to be associated with the surname Flood.
-
A.
Brendan Flood
Brendan Flood is a British businessman best known for his involvement in football club ownership and property development.
-
B.
Tim Fywell
Tim Fywell is a British film and television director known for his work on literary adaptations and period dramas.
-
C.
Keith Fenton
Keith Fenton is the charming yet unfaithful boyfriend whose behavior sparks the romantic mind games at the center of the film "Two Can Play That Game."
-
D.
Brian Frosh
Brian Frosh is an American lawyer and Democratic politician who served as the Attorney General of Maryland from 2015 to 2023.
-
E.
Tony Britton
Tony Britton was a British actor known for his extensive work in film, television, and theatre from the mid-20th century onward.
- 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_69d85cd64d108190853797a95c11cc45 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69dedee50afc8190bf7b0f4bbe8c60a3 |
completed | April 15, 2026, 12:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69feb7dd767c8190a129f00303f970bc |
completed | May 9, 2026, 4:28 a.m. |
| NEDg | Description generation | batch_69febbe8125081908bab0c91af6fb6d2 |
completed | May 9, 2026, 4:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69febd10a9a08190aabfa072199db5c9 |
completed | May 9, 2026, 4:50 a.m. |
Created at: April 10, 2026, 3:01 a.m.