Triple
T26474974
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UT3 |
E666001
|
entity |
| Predicate | hasCollectingArea |
P14087
|
FINISHED |
| Object | approximately 52.8 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: approximately 52.8 square meters | Statement: [UT3, hasCollectingArea, approximately 52.8 square meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCollectingArea Context triple: [UT3, hasCollectingArea, approximately 52.8 square meters]
-
A.
hasCollectionArea
Indicates that an entity is associated with a specific geographic or spatial area from which items, specimens, or data are collected.
-
B.
collectingArea
chosen
Indicates the total surface area over which something (typically a device or system) gathers or receives a substance, signal, or resource.
-
C.
collectingAreaEquivalent
Indicates that two entities have collecting areas that are equal in size or effectively equivalent for the purpose of collection.
-
D.
hasCollector
Indicates that an entity is associated with, or owned/curated by, a specific collector.
-
E.
canCollect
Indicates that one entity has the ability or permission to gather, receive, or take possession of 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_69ee883f80dc819090e311b022b78e02 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69fdd5fba5048190b7d430ae2054a1fd |
completed | May 8, 2026, 12:24 p.m. |
| PD | Predicate disambiguation | batch_69fdd35f76f88190a1854ea27132f9c7 |
completed | May 8, 2026, 12:13 p.m. |
Created at: April 27, 2026, 12:22 a.m.