Triple
T21202079
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Belogorsky Fortress |
E522478
|
entity |
| Predicate | functionInFiction |
P135758
|
FINISHED |
| Object | military outpost |
—
|
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: military outpost | Statement: [Belogorsky Fortress, functionInFiction, military outpost]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: functionInFiction Context triple: [Belogorsky Fortress, functionInFiction, military outpost]
-
A.
functionInLiterature
chosen
Indicates that one entity serves a particular narrative, rhetorical, or thematic role within a literary work in relation to another entity.
-
B.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
C.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
D.
conductsInFiction
Indicates that an entity carries out or performs an action or role within a fictional context or narrative.
-
E.
fictionalContent
Indicates that one entity is content whose subject matter, events, or characters are imaginary or invented rather than factual.
- 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_69e0b5112d8881909510b2dcdc93106d |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e73431973c81908c8682d7808a9d13 |
completed | April 21, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69e5f6094e3c81909ee9699e00d371f7 |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3:18 p.m.