Triple
T1001012
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Four Worlds |
E21601
|
entity |
| Predicate | includesPhysicalWorld |
P22160
|
FINISHED |
| Object | physical aspect of Assiyah |
—
|
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: physical aspect of Assiyah | Statement: [Four Worlds, includesPhysicalWorld, physical aspect of Assiyah]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesPhysicalWorld Context triple: [Four Worlds, includesPhysicalWorld, physical aspect of Assiyah]
-
A.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
B.
publicPerception
Indicates how an individual, group, or entity is viewed, judged, or regarded by the general public or society at large.
-
C.
viewOnReality
Indicates a subject’s overarching perspective, interpretation, or conceptual stance regarding the nature of reality.
-
D.
involvedPhysicalEffect
Indicates that one entity participates in causing, experiencing, or mediating a physical effect on another entity or the environment.
-
E.
usedWorldwide
Indicates that something is utilized or applied across many countries or regions around the world.
- F. None of above. chosen
Provenance (4 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_69a493c53e648190ae8cb76c433fd9a7 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4fb18b88190ae2d620aaaff4f90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2b1f4f88190822598cfd2a0fd2b |
completed | March 1, 2026, 9:42 p.m. |
| PDg | Predicate description generation | batch_69a4b36064a48190b85c402f32cbadd1 |
completed | March 1, 2026, 9:45 p.m. |
Created at: March 1, 2026, 7:41 p.m.