Triple
T14691007
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Caliban |
E345031
|
entity |
| Predicate | associatedWith |
P37
|
FINISHED |
| Object | Stephano |
E352330
|
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: Stephano | Statement: [Caliban, associatedWith, Stephano]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephano Context triple: [Caliban, associatedWith, Stephano]
-
A.
Stephano
chosen
Stephano is a comical, drunken butler in William Shakespeare’s play "The Tempest," known for his foolish schemes and slapstick antics.
-
B.
Stephano
Stephano is a false identity adopted by the villainous Count Olaf in Lemony Snicket’s "A Series of Unfortunate Events" to deceive and manipulate the Baudelaire orphans.
-
C.
Timoteo
Timoteo is a masculine given name, commonly used in Romance-language countries, derived from the biblical name Timothy.
-
D.
Dionisio
Dionisio is a masculine given name of Greek origin, derived from Dionysius and associated with the ancient Greek god Dionysus.
-
E.
Archibaldo
Archibaldo is a Muppet character from the Mexican adaptation of Sesame Street, Plaza Sésamo, known for his formal, somewhat pompous personality.
- 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_69d822e34b348190ada4d1cdb6c7c226 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb585d46c81908d6964130914cec4 |
completed | April 14, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fde189771c81909289b8b044e32547 |
completed | May 8, 2026, 1:13 p.m. |
Created at: April 10, 2026, 1:28 a.m.