Triple
T490651
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Giant Magellan Telescope |
E9980
|
entity |
| Predicate | collectingArea |
P14087
|
FINISHED |
| Object | ~368 square meters |
—
|
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: ~368 square meters | Statement: [Giant Magellan Telescope, collectingArea, ~368 square meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: collectingArea Context triple: [Giant Magellan Telescope, collectingArea, ~368 square meters]
-
A.
collects
Indicates that one entity gathers, accumulates, or brings together one or more other entities into its possession or control.
-
B.
hasExhibitionArea
Indicates that an entity includes or provides a designated space or area for exhibitions or displays.
-
C.
collectibleAspect
Indicates that one entity represents a collectible-related characteristic, feature, or dimension associated with another entity.
-
D.
collectsFrom
Indicates that one entity gathers, receives, or takes something (such as items, data, or payments) from another entity.
-
E.
connectsArea
Indicates that one area serves as a link or passage between two other areas, enabling movement or interaction between them.
- 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_69a2e802e2908190ab17c9479e0b6412 |
completed | Feb. 28, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69a2f0e22a308190b04d12974fd08a38 |
completed | Feb. 28, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69a2edf7ce008190836fb6ab5ea39375 |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eebb2c908190960a4d0c014304cd |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:12 p.m.