Triple
T71021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mule deer |
E1420
|
entity |
| Predicate | antlerCycle |
P3835
|
FINISHED |
| Object | antlers shed and regrown annually |
—
|
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: antlers shed and regrown annually | Statement: [mule deer, antlerCycle, antlers shed and regrown annually]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antlerCycle Context triple: [mule deer, antlerCycle, antlers shed and regrown annually]
-
A.
hasRailTrail
Indicates that one location or entity possesses, includes, or is connected by a rail trail (a recreational trail converted from or running along a former or existing railway corridor) to another location or entity.
-
B.
hasBicycleFacilities
Indicates that appropriate bicycle-related infrastructure or amenities are available at or associated with the subject.
-
C.
wears
Indicates that one entity is dressed in, or has on its body, a particular item such as clothing or accessories.
-
D.
carriedBy
Indicates that one entity is physically supported and transported by another entity.
-
E.
transports
Indicates that one entity carries or conveys another entity from one place to another.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
| PDg | Predicate description generation | batch_69a24fcf5a88819088c5fa4c08476358 |
completed | Feb. 28, 2026, 2:15 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.