Triple
T30711802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Medusa |
E781913
|
entity |
| Predicate | secrecyLevelInFiction |
P61556
|
FINISHED |
| Object | top secret |
—
|
LITERAL 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: top secret | Statement: [Medusa, secrecyLevelInFiction, top secret]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secrecyLevelInFiction Context triple: [Medusa, secrecyLevelInFiction, top secret]
-
A.
fictionalSecurityLevel
chosen
Indicates the degree or category of security status assigned within a fictional or imagined context.
-
B.
fictionalizationLevel
Indicates the degree to which an event, account, or representation has been altered, embellished, or invented relative to factual reality.
-
C.
hasTypeOfSecrecy
Indicates that something is associated with a particular kind or level of secrecy.
-
D.
hasSecretLevel
Indicates that an entity is associated with a particular secrecy or security classification level.
-
E.
guardedByInFiction
Indicates that one fictional entity is protected or watched over by another within a narrative context.
- F. None of above.
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_69f224acd24481908ed5f96f0d69b5dd |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f68c1efe608190a382d57a3aa3f542 |
completed | May 2, 2026, 11:43 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:35 p.m.