Triple
T7009991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ezequiel Barco |
E162555
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Barco
Barco is a surname most notably associated with Argentine professional footballer Ezequiel Barco.
|
E635491
|
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: Barco | Statement: [Ezequiel Barco, familyName, Barco]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Barco Context triple: [Ezequiel Barco, familyName, Barco]
-
A.
Hensoldt
Hensoldt is a German defense and security electronics company specializing in advanced sensor solutions such as radars, optronics, and electronic warfare systems.
-
B.
Apogee, Inc.
Apogee, Inc. is a visual effects company established by Academy Award–winning special effects artist John Dykstra, known for its pioneering work in film visual effects.
-
C.
Avisio
Avisio is a river in northern Italy that flows through the Trentino region before joining the Adige.
-
D.
Diehl
Diehl is the middle name of Newton D. Baker, an American lawyer and politician who served as U.S. Secretary of War during World War I.
-
E.
Whelen Engineering
Whelen Engineering is an American company that designs and manufactures emergency warning lights, sirens, and related safety systems for police, fire, EMS, and other public safety and automotive applications.
- 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: Barco Triple: [Ezequiel Barco, familyName, Barco]
Generated description
Barco is a surname most notably associated with Argentine professional footballer Ezequiel Barco.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Barco Target entity description: Barco is a surname most notably associated with Argentine professional footballer Ezequiel Barco.
-
A.
Hensoldt
Hensoldt is a German defense and security electronics company specializing in advanced sensor solutions such as radars, optronics, and electronic warfare systems.
-
B.
Apogee, Inc.
Apogee, Inc. is a visual effects company established by Academy Award–winning special effects artist John Dykstra, known for its pioneering work in film visual effects.
-
C.
Avisio
Avisio is a river in northern Italy that flows through the Trentino region before joining the Adige.
-
D.
Diehl
Diehl is the middle name of Newton D. Baker, an American lawyer and politician who served as U.S. Secretary of War during World War I.
-
E.
Whelen Engineering
Whelen Engineering is an American company that designs and manufactures emergency warning lights, sirens, and related safety systems for police, fire, EMS, and other public safety and automotive applications.
- 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_69c6885928148190ae31909fbb5e9849 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dc3917c481909a288c3e56630c48 |
completed | March 27, 2026, 7:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c76a47aa6481908ac0039b2b728edb |
completed | March 28, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69c76b67fc48819088ba80f1f84aa2f0 |
completed | March 28, 2026, 5:47 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c76c46f9308190a7a1f0aa5284cef4 |
completed | March 28, 2026, 5:51 a.m. |
Created at: March 27, 2026, 2:34 p.m.