Triple
T36962329
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitecliff |
E914339
|
entity |
| Predicate | inFictionalWorld |
P3758
|
FINISHED |
| Object | Empire of the Isles |
—
|
NE NERFINISHED |
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: Empire of the Isles | Statement: [Whitecliff, inFictionalWorld, Empire of the Isles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inFictionalWorld Context triple: [Whitecliff, inFictionalWorld, Empire of the Isles]
-
A.
fictionalUniverse
chosen
Indicates that two entities exist within, or are associated with, the same fictional universe or narrative setting.
-
B.
fictionalUniverseCreated
Indicates that one entity is the creator or originator of a particular fictional universe or setting in which stories or works take place.
-
C.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
D.
fictionalContent
Indicates that one entity is content whose subject matter, events, or characters are imaginary or invented rather than factual.
-
E.
createsInFiction
Indicates that one entity is the creator or originator of another entity within a fictional or 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_69f76e8c498c8190b2842db80aea8b3b |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
Created at: May 3, 2026, 4:14 p.m.