Triple
T7695978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manalo |
E174370
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Nash Aguas
Nash Aguas is a Filipino actor and former child star best known for his work in Philippine television and film.
|
E683552
|
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: Nash Aguas | Statement: [Manalo, hasNotableBearer, Nash Aguas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nash Aguas Context triple: [Manalo, hasNotableBearer, Nash Aguas]
-
A.
Fuente Vaqueros
Fuente Vaqueros is a small village in the province of Granada, Spain, best known as the birthplace of the renowned poet and playwright Federico García Lorca.
-
B.
Palo Seco
Palo Seco is a coastal barrio of the municipality of Toa Baja in Puerto Rico, known for its small residential community and proximity to San Juan Bay.
-
C.
Pedernales
Pedernales is a coastal town in northwestern Ecuador known for its beaches and fishing activities.
-
D.
Rio Fuerte
Rio Fuerte is a major river in northwestern Mexico that carves through the Sierra Madre Occidental and helps form the dramatic landscapes of the Copper Canyon region.
-
E.
De Canas
De Canas is a party to the U.S. Supreme Court case De Canas v. Bica, which addressed the extent of state authority over the employment of unauthorized immigrants.
- 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: Nash Aguas Triple: [Manalo, hasNotableBearer, Nash Aguas]
Generated description
Nash Aguas is a Filipino actor and former child star best known for his work in Philippine television and film.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nash Aguas Target entity description: Nash Aguas is a Filipino actor and former child star best known for his work in Philippine television and film.
-
A.
Fuente Vaqueros
Fuente Vaqueros is a small village in the province of Granada, Spain, best known as the birthplace of the renowned poet and playwright Federico García Lorca.
-
B.
Palo Seco
Palo Seco is a coastal barrio of the municipality of Toa Baja in Puerto Rico, known for its small residential community and proximity to San Juan Bay.
-
C.
Pedernales
Pedernales is a coastal town in northwestern Ecuador known for its beaches and fishing activities.
-
D.
Rio Fuerte
Rio Fuerte is a major river in northwestern Mexico that carves through the Sierra Madre Occidental and helps form the dramatic landscapes of the Copper Canyon region.
-
E.
De Canas
De Canas is a party to the U.S. Supreme Court case De Canas v. Bica, which addressed the extent of state authority over the employment of unauthorized immigrants.
- 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_69c6995966348190939e6c37ba272c06 |
completed | March 27, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69c70267dab88190ac8e3f643343bf13 |
completed | March 27, 2026, 10:19 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8acaa6004819088f1ae45ad9b378e |
completed | March 29, 2026, 4:38 a.m. |
| NEDg | Description generation | batch_69c8adf82b5481908bb556a15ff942fd |
completed | March 29, 2026, 4:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c8ae9096ac8190af6fdfbfc35200cd |
completed | March 29, 2026, 4:46 a.m. |
Created at: March 27, 2026, 4:03 p.m.