Triple
T37513825
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durance of Hate |
E932579
|
entity |
| Predicate | tileSetType |
P188191
|
FINISHED |
| Object | temple dungeon |
—
|
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: temple dungeon | Statement: [Durance of Hate, tileSetType, temple dungeon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tileSetType Context triple: [Durance of Hate, tileSetType, temple dungeon]
-
A.
tilesetStyle
chosen
Indicates the visual design or stylistic configuration applied to a set of tiles in a tiled layout or map.
-
B.
tessellationType
Indicates the specific pattern or method by which shapes repeatedly cover a surface without gaps or overlaps.
-
C.
typeOfSets
Indicates that one entity specifies or classifies the kind or category of sets to which another entity belongs.
-
D.
turfType
Indicates the specific kind or category of turf (e.g., grass, artificial) associated with an entity or location.
-
E.
textureType
Indicates the specific kind or category of surface quality or feel that characterizes an 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_69f76ec730988190b5aa4f9cb9afd518 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbacaf54648190811ea33b34907e8e |
completed | May 6, 2026, 9:03 p.m. |
| PD | Predicate disambiguation | batch_69fba883f770819091059c6f6c6af9f7 |
completed | May 6, 2026, 8:45 p.m. |
Created at: May 3, 2026, 4:17 p.m.