Triple
T6140978
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | José Pérez San Román |
E136959
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
San Román
San Román is a Spanish surname commonly borne by individuals of Hispanic origin.
|
E570859
|
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: San Román | Statement: [José Pérez San Román, familyName, San Román]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: San Román Context triple: [José Pérez San Román, familyName, San Román]
-
A.
San Marcelino
San Marcelino is a landlocked municipality in the province of Zambales in the Philippines, known for its agricultural economy and proximity to the Subic Bay area.
-
B.
San Martín de la Vega
San Martín de la Vega is a municipality in the Community of Madrid, Spain, known for hosting the Parque Warner Madrid theme park.
-
C.
Olmedo
Olmedo is a small town in the Gallura region of northern Sardinia, Italy, known for its rural character and traditional Sardinian culture.
-
D.
San Martín de Trevejo
San Martín de Trevejo is a small municipality in western Spain’s Extremadura region, noted for its unique local culture and preservation of the minority Fala language.
-
E.
Caseres
Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
- 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: San Román Triple: [José Pérez San Román, familyName, San Román]
Generated description
San Román is a Spanish surname commonly borne by individuals of Hispanic origin.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: San Román Target entity description: San Román is a Spanish surname commonly borne by individuals of Hispanic origin.
-
A.
San Marcelino
San Marcelino is a landlocked municipality in the province of Zambales in the Philippines, known for its agricultural economy and proximity to the Subic Bay area.
-
B.
San Martín de la Vega
San Martín de la Vega is a municipality in the Community of Madrid, Spain, known for hosting the Parque Warner Madrid theme park.
-
C.
Olmedo
Olmedo is a small town in the Gallura region of northern Sardinia, Italy, known for its rural character and traditional Sardinian culture.
-
D.
San Martín de Trevejo
San Martín de Trevejo is a small municipality in western Spain’s Extremadura region, noted for its unique local culture and preservation of the minority Fala language.
-
E.
Caseres
Caseres is a small rural municipality located in the Terra Alta comarca of Catalonia, Spain, known for its agricultural landscape and traditional village character.
- 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_69c008a179388190a3b5a081bbf46d55 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c05cb2404c8190bbbfa78d5f49389f |
completed | March 22, 2026, 9:18 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c135f2defc8190a666f82e230a51c2 |
completed | March 23, 2026, 12:45 p.m. |
| NEDg | Description generation | batch_69c13679dd58819099036d1119fa370b |
completed | March 23, 2026, 12:47 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c1376db6a0819087c0d0aebc2e2b3e |
completed | March 23, 2026, 12:51 p.m. |
Created at: March 22, 2026, 4:16 p.m.