Triple
T38509740
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | European pine marten |
E921868
|
entity |
| Predicate | usesDenSites |
P62923
|
FINISHED |
| Object | tree cavities |
—
|
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: tree cavities | Statement: [European pine marten, usesDenSites, tree cavities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDenSites Context triple: [European pine marten, usesDenSites, tree cavities]
-
A.
hasSiteUse
chosen
Indicates that a site is used or designated for a particular function, activity, or purpose.
-
B.
usedOnWebsites
Indicates that something is employed or implemented as part of the content, functionality, or infrastructure of websites.
-
C.
hasProtectedSites
Indicates that an entity possesses, manages, or includes one or more sites that are designated as protected areas.
-
D.
containsSite
Indicates that one entity spatially or structurally includes another entity as a site or location within its bounds.
-
E.
numberOfSites
Indicates the total count of distinct sites associated with or involved in the given entity or context.
- 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_69f76ea3c5448190aa7002fc1ba3f874 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fcdf2394748190b35cead3e208447d |
completed | May 7, 2026, 6:51 p.m. |
| PD | Predicate disambiguation | batch_69fcdbe344ec8190a0471911952f4b82 |
completed | May 7, 2026, 6:37 p.m. |
Created at: May 3, 2026, 4:32 p.m.