Triple
T7975627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santiago |
E185438
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Tiago |
E17210
|
NE FINISHED |
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: Tiago | Statement: [Santiago, hasVariant, Tiago]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tiago Context triple: [Santiago, hasVariant, Tiago]
-
A.
Tiago
chosen
Tiago is a masculine given name commonly used in Portuguese-speaking countries, often considered a variant of the name James.
-
B.
Damião
Damião is a Portuguese given name, equivalent to Damian, commonly used in Lusophone countries.
-
C.
Diogo
Diogo is a masculine given name, commonly used in Portuguese-speaking countries and related to the name Diego.
-
D.
Diego
Diego is a given name of Spanish origin commonly used in Spanish-speaking countries and beyond.
-
E.
Lúcio
Lúcio is a Brazilian architect and urban planner best known as the principal designer of Brasília, the country’s modernist capital city.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca829851908190b4e03829353ee7c3 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3bf56f688190902b95afe42635ec |
completed | March 31, 2026, 3:13 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc5677968881908835169157244962 |
completed | March 31, 2026, 11:19 p.m. |
Created at: March 30, 2026, 5:14 p.m.