Triple
T2317682
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Houston Dynamo |
E51102
|
entity |
| Predicate | formerOwner |
P347
|
FINISHED |
| Object |
Gabriel Brener
Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
|
E256520
|
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: Gabriel Brener | Statement: [Houston Dynamo, formerOwner, Gabriel Brener]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gabriel Brener Context triple: [Houston Dynamo, formerOwner, Gabriel Brener]
-
A.
David Brenner
David Brenner was an American film editor known for his work on major Hollywood blockbusters, including several of director Zack Snyder’s films.
-
B.
Gregory Rabassa
Gregory Rabassa was an acclaimed American literary translator best known for bringing major works of Latin American fiction, including Gabriel García Márquez’s novels, into English.
-
C.
Gil Avérous
Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
-
D.
Joel Stransky
Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
-
E.
Sebastian Maltz
Sebastian Maltz is an actor known for his role in the television drama series "Patrick Melrose."
- 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: Gabriel Brener Triple: [Houston Dynamo, formerOwner, Gabriel Brener]
Generated description
Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Gabriel Brener Target entity description: Gabriel Brener is a businessman and investor best known in sports for his former ownership stake in Major League Soccer’s Houston Dynamo.
-
A.
David Brenner
David Brenner was an American film editor known for his work on major Hollywood blockbusters, including several of director Zack Snyder’s films.
-
B.
Gregory Rabassa
Gregory Rabassa was an acclaimed American literary translator best known for bringing major works of Latin American fiction, including Gabriel García Márquez’s novels, into English.
-
C.
Gil Avérous
Gil Avérous is a French politician who serves as the mayor of the city of Châteauroux.
-
D.
Joel Stransky
Joel Stransky is a former South African rugby union fly-half best known for kicking the winning drop goal in the 1995 Rugby World Cup final.
-
E.
Sebastian Maltz
Sebastian Maltz is an actor known for his role in the television drama series "Patrick Melrose."
- 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_69a88b074b908190ae983dbca7757d88 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc62fa60c8190b4859ce296ea4177 |
completed | March 7, 2026, 6:31 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae8964902081909070dd03ccb7cf1f |
completed | March 9, 2026, 8:48 a.m. |
| NEDg | Description generation | batch_69ae8ab5bf78819085120418a26cbe28 |
completed | March 9, 2026, 8:54 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae8b2a89788190975ab66f432f834f |
completed | March 9, 2026, 8:56 a.m. |
Created at: March 4, 2026, 7:49 p.m.