Triple
T249969
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pan troglodytes |
E5120
|
entity |
| Predicate | toolUseExamples |
P8562
|
FINISHED |
| Object | termite fishing with sticks |
—
|
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: termite fishing with sticks | Statement: [Pan troglodytes, toolUseExamples, termite fishing with sticks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: toolUseExamples Context triple: [Pan troglodytes, toolUseExamples, termite fishing with sticks]
-
A.
coPilotWith
Indicates that two entities jointly serve as pilots or share piloting responsibilities for the same vehicle or mission.
-
B.
coPilotOf
Indicates that one entity serves as the co-pilot assisting and supporting another entity in operating or navigating a vehicle or craft.
-
C.
hasExample
Indicates that one entity serves as an instance, illustration, or concrete example of another entity.
-
D.
usageType
Indicates the specific manner, purpose, or context in which something is used or intended to be used.
-
E.
usedWith
Indicates that one entity is typically or appropriately employed together with another entity in a combined or complementary use.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d3728f0819086214ccc2db2305a |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
| PDg | Predicate description generation | batch_69a25c036b54819090a101c4cbdbcff7 |
completed | Feb. 28, 2026, 3:07 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.