Triple
T33598572
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Summerdown Comprehensive School |
E860644
|
entity |
| Predicate | fictionalFeature |
P103336
|
FINISHED |
| Object | staff room |
—
|
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: staff room | Statement: [Summerdown Comprehensive School, fictionalFeature, staff room]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalFeature Context triple: [Summerdown Comprehensive School, fictionalFeature, staff room]
-
A.
fictionalType
Indicates that one entity is a fictional or imaginary type or category of the other entity.
-
B.
fictionalFocus
Indicates that the primary emphasis or attention within a context is placed on fictional content, elements, or aspects.
-
C.
fictionalGenre
Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
-
D.
notableFictionalFeature
chosen
Indicates that an entity is distinguished by a specific fictional characteristic, trait, or element it is known for.
-
E.
fictionalOrigin
Indicates that one entity originates from, or was first introduced within, a fictional work, universe, or narrative created by another entity.
- 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_69f3497f35908190a2e9bbb9b96c7a3f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fe86cad5108190b0164b8bc6fc23ea |
completed | May 9, 2026, 12:58 a.m. |
| PD | Predicate disambiguation | batch_69fe83c0c9888190b6fc40c7f727b569 |
completed | May 9, 2026, 12:45 a.m. |
Created at: May 1, 2026, 1:41 a.m.