Triple
T17687208
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrews |
E440925
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Andres |
—
|
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: Andres | Statement: [Andrews, hasVariant, Andres]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andres Context triple: [Andrews, hasVariant, Andres]
-
A.
Andrés
chosen
Andrés is a Spanish given name commonly used as the equivalent of Andrew.
-
B.
Jo Andres
Jo Andres was an American filmmaker, choreographer, and artist known for her experimental films and multimedia performance work.
-
C.
Don Andrea
Don Andrea is a ghostly nobleman whose murder and quest for vengeance set the tragic events of Thomas Kyd’s Elizabethan revenge play *The Spanish Tragedy* into motion.
-
D.
Jorge
Jorge is a masculine given name of Spanish and Portuguese origin, equivalent to George in English.
-
E.
Jorge
Jorge is the central character of Robert Silverberg’s science fiction novella "Born with the Dead," set in a future where the dead can be partially revived and live apart from the living.
- 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_69d8b9e940b081908b862bb0e6e89b0d |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e470488c4081909b747313ef97b69c |
completed | April 19, 2026, 6:03 a.m. |
Created at: April 10, 2026, 10:03 a.m.