Triple
T9856261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Underwater Dome |
E239594
|
entity |
| Predicate | hasViewingAngle |
P88621
|
FINISHED |
| Object | 360 degrees |
—
|
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: 360 degrees | Statement: [Underwater Dome, hasViewingAngle, 360 degrees]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewingAngle Context triple: [Underwater Dome, hasViewingAngle, 360 degrees]
-
A.
hasViewingAngles
chosen
Indicates that one entity possesses or is characterized by specific viewing angles relative to another entity or reference frame.
-
B.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
C.
hasViewingSide
Indicates that one entity serves as the side or surface of another entity that is intended to be viewed or observed.
-
D.
viewingIs
Indicates that one entity is engaged in the act or state of viewing, observing, or watching another entity.
-
E.
hasViewThrough
Indicates that one entity can be seen or visually perceived through another entity acting as an intermediate medium or opening.
- 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_69ca84e6493081909cf58c8d42ea856b |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb39719288190adf45e7c029edd51 |
completed | April 2, 2026, 12:08 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:35 p.m.