Triple
T17975904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christophoros |
E449469
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Cristóbal |
—
|
NE NERFINISHED |
How this triple was built (2 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: Cristóbal | Statement: [Christophoros, hasVariant, Cristóbal]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cristóbal Context triple: [Christophoros, hasVariant, Cristóbal]
-
A.
Cristóbal
chosen
Cristóbal is the Spanish given name equivalent to Christopher, commonly used in Spanish-speaking countries.
-
B.
Bartolomé
Bartolomé is the namesake of Bartolomé House, likely a historically or academically significant figure associated with that building.
-
C.
Guillermo
Guillermo is the Spanish form of the given name William, commonly used in Spanish-speaking countries.
-
D.
Colón
Colón is a Spanish-origin surname commonly found in Hispanic communities and notably borne by figures such as comic book artist Ernie Colón.
-
E.
Colón
Colón is a riverside city in Argentina known for its tourism, hot springs, and access to the Uruguay River.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b9f9927c8190a006110c8b996e61 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4b1fee86c8190a9a220b008e78e10 |
completed | April 19, 2026, 10:44 a.m. |
Created at: April 10, 2026, 10:22 a.m.