Triple
T17173488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bartolomé House |
E416796
|
entity |
| Predicate | namedAfter |
P63
|
FINISHED |
| Object |
Bartolomé
Bartolomé is the namesake of Bartolomé House, likely a historically or academically significant figure associated with that building.
|
E1253388
|
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: Bartolomé | Statement: [Bartolomé House, namedAfter, Bartolomé]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bartolomé Context triple: [Bartolomé House, namedAfter, Bartolomé]
-
A.
Bartolomeo
Bartolomeo is a masculine Italian given name historically borne by several notable figures, including artists, architects, and explorers.
-
B.
Diego de Valdés
Diego de Valdés was a Spanish nobleman and military figure from the influential Valdés family, active during the late Middle Ages.
-
C.
Gutierre
Gutierre is a Spanish given name, historically used in medieval Iberia and related to names like Walter.
-
D.
Diego de Santa María
Diego de Santa María was a Spanish Dominican friar and educator best known for establishing the Colegio de San Juan de Letran in the Philippines.
-
E.
Diego de León
Diego de León is a Madrid Metro station and major interchange hub in the Salamanca district of Madrid, Spain.
- 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: Bartolomé Triple: [Bartolomé House, namedAfter, Bartolomé]
Generated description
Bartolomé is the namesake of Bartolomé House, likely a historically or academically significant figure associated with that building.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bartolomé Target entity description: Bartolomé is the namesake of Bartolomé House, likely a historically or academically significant figure associated with that building.
-
A.
Bartolomeo
Bartolomeo is a masculine Italian given name historically borne by several notable figures, including artists, architects, and explorers.
-
B.
Diego de Valdés
Diego de Valdés was a Spanish nobleman and military figure from the influential Valdés family, active during the late Middle Ages.
-
C.
Gutierre
Gutierre is a Spanish given name, historically used in medieval Iberia and related to names like Walter.
-
D.
Diego de Santa María
Diego de Santa María was a Spanish Dominican friar and educator best known for establishing the Colegio de San Juan de Letran in the Philippines.
-
E.
Diego de León
Diego de León is a Madrid Metro station and major interchange hub in the Salamanca district of Madrid, Spain.
- 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_69d886d5f34c8190b24564dfaa63f3fb |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3fc0b7c9c819082e503cb493d7e7b |
completed | April 18, 2026, 9:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0148415c788190a4248b097f323d03 |
completed | May 11, 2026, 3:08 a.m. |
| NEDg | Description generation | batch_6a0148efb45081908734c785d8fb833a |
completed | May 11, 2026, 3:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a01495631588190a0670ca71dee7b36 |
completed | May 11, 2026, 3:13 a.m. |
Created at: April 10, 2026, 5:37 a.m.