Triple
T15875993
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vis and Ramin |
E384954
|
entity |
| Predicate | hasMainCharacter |
P1183
|
FINISHED |
| Object | Vis |
E547727
|
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: Vis | Statement: [Vis and Ramin, hasMainCharacter, Vis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vis Context triple: [Vis and Ramin, hasMainCharacter, Vis]
-
A.
Vis
Vis is a Croatian island in the Adriatic Sea known for its unspoiled nature, historic towns, and former role as a strategic military base.
-
B.
VIS
VIS is the IATA airport code for Visalia Municipal Airport in Visalia, California, United States.
-
C.
VIS
VIS is a large-scale European Union database system used to store and exchange visa application and related biometric data among member states’ authorities.
-
D.
Vin
Vin is a common shortened form of the given name Vincent, often used as an informal or familiar nickname.
-
E.
Vis a vis
chosen
Vis a vis is a Spanish prison drama television series that follows the transformation of a naive young woman after she is incarcerated in a high-security women’s prison.
- 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_69d86da4e86481909f1325fdc971b5ec |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e155fdc1b881909d1c82c4c66a195a |
completed | April 16, 2026, 9:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffa94e9b548190bec74e6d9790d241 |
completed | May 9, 2026, 9:38 p.m. |
Created at: April 10, 2026, 4:51 a.m.