Triple
T24814350
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miguel García |
E620872
|
entity |
| Predicate | hasGivenNameEquivalence |
P157373
|
FINISHED |
| Object | Miguel corresponds to Michael in English |
—
|
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: Miguel corresponds to Michael in English | Statement: [Miguel García, hasGivenNameEquivalence, Miguel corresponds to Michael in English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGivenNameEquivalence Context triple: [Miguel García, hasGivenNameEquivalence, Miguel corresponds to Michael in English]
-
A.
hasGivenNameTo
Indicates that one entity has assigned or provided a given (first) name to another entity.
-
B.
hasEquivalent
Indicates that two entities are considered equal in value, meaning, or function within a given context.
-
C.
hasGivenNameUsage
Indicates that an entity is associated with a particular way or context in which its given name is used.
-
D.
hasNameGivenTo
Indicates that one entity is the name that has been assigned or given to another entity.
-
E.
hasGivenNameBasis
Indicates that one entity’s given name is derived from, based on, or formed using another entity (such as a name, word, or person) as its basis.
- F. None of above. chosen
Provenance (4 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f42d9000b8819081ea2605f3c193d6 |
completed | May 1, 2026, 4:35 a.m. |
| PD | Predicate disambiguation | batch_69f420f471a0819095a6cd24ed8f7476 |
completed | May 1, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f42b11251881908070b93355de64ad |
completed | May 1, 2026, 4:24 a.m. |
Created at: April 18, 2026, 5 a.m.