Triple
T10972453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Victor Frankenstein |
E259275
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Victor |
E30470
|
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: Victor | Statement: [Victor Frankenstein, givenName, Victor]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Victor Context triple: [Victor Frankenstein, givenName, Victor]
-
A.
Victor
chosen
Victor is a masculine given name of Latin origin meaning "conqueror" or "winner," commonly used in many European and English-speaking countries.
-
B.
Victor
Victor is a central character in the TV series "Dollhouse," known as one of the programmable "Actives" whose identity and memories are repeatedly altered for various missions.
-
C.
Victor
Victor is a character in Gregory Benford’s science fiction novel "Timescape," which explores time communication and ecological catastrophe.
-
D.
Victor
Victor is the NATO reporting name for a class of Soviet nuclear-powered attack submarines developed during the Cold War.
-
E.
Victor
Victor is a trusted henchman and enforcer for drug kingpin Gustavo Fring in the television series Breaking Bad.
- 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_69d6aa895f4c8190887a15460ef622f4 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7719b5edc81908c1019f81e78bd2e |
completed | April 9, 2026, 9:30 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e2d7a0b3dc819084fbda3227caf5b5 |
completed | April 18, 2026, 1 a.m. |
Created at: April 8, 2026, 9:24 p.m.