Triple
T16174816
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rémi Ochlik Award |
E392535
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object |
Manu Brabo
Manu Brabo is a Spanish photojournalist renowned for his frontline coverage of conflicts in the Middle East and North Africa.
|
E1197669
|
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: Manu Brabo | Statement: [Rémi Ochlik Award, notableRecipient, Manu Brabo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Manu Brabo Context triple: [Rémi Ochlik Award, notableRecipient, Manu Brabo]
-
A.
Suraci
Suraci is an Italian surname associated with individuals such as Anna Suraci Benedetto.
-
B.
Wilder Guisao
Wilder Guisao is a Colombian professional footballer known for playing as a winger for clubs in South America and abroad.
-
C.
Marcelo
Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
-
D.
Tarcisio
Tarcisio is an Italian given name most notably borne by Cardinal Tarcisio Bertone, a prominent Vatican official and former Secretary of State of the Holy See.
-
E.
Marcio
Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
- 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: Manu Brabo Triple: [Rémi Ochlik Award, notableRecipient, Manu Brabo]
Generated description
Manu Brabo is a Spanish photojournalist renowned for his frontline coverage of conflicts in the Middle East and North Africa.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Manu Brabo Target entity description: Manu Brabo is a Spanish photojournalist renowned for his frontline coverage of conflicts in the Middle East and North Africa.
-
A.
Suraci
Suraci is an Italian surname associated with individuals such as Anna Suraci Benedetto.
-
B.
Wilder Guisao
Wilder Guisao is a Colombian professional footballer known for playing as a winger for clubs in South America and abroad.
-
C.
Marcelo
Marcelo is a common Portuguese and Spanish given name, notably borne by figures such as Brazilian footballer Marcelo Vieira and former Portuguese Prime Minister Marcelo Caetano.
-
D.
Tarcisio
Tarcisio is an Italian given name most notably borne by Cardinal Tarcisio Bertone, a prominent Vatican official and former Secretary of State of the Holy See.
-
E.
Marcio
Marcio is a masculine given name commonly used in Portuguese- and Spanish-speaking countries, derived from the Latin name Marcius.
- 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_69d87f1d32208190942e4e499a80c18c |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e21ebab54c81908d82dd6a26c406c2 |
completed | April 17, 2026, 11:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff7bfc3ac819082596cc533c5faa4 |
completed | May 10, 2026, 3:13 a.m. |
| NEDg | Description generation | batch_69fff8bc4f7c81908f7e9ffaa9f3cfb1 |
completed | May 10, 2026, 3:17 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fff94cd32081908205ae383e58d148 |
completed | May 10, 2026, 3:19 a.m. |
Created at: April 10, 2026, 5:02 a.m.