Triple
T3995063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camponotus pennsylvanicus |
E87078
|
entity |
| Predicate | bodySegments |
P21283
|
FINISHED |
| Object | head, mesosoma, metasoma |
—
|
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: head, mesosoma, metasoma | Statement: [Camponotus pennsylvanicus, bodySegments, head, mesosoma, metasoma]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bodySegments Context triple: [Camponotus pennsylvanicus, bodySegments, head, mesosoma, metasoma]
-
A.
bodyPattern
Indicates a recurring or characteristic configuration, arrangement, or sequence exhibited by a body or physical form.
-
B.
body
Indicates that one entity is the physical body or main corporeal form of another entity.
-
C.
bodyLevel
Indicates the relative position or height of an entity’s body (or body part) along a vertical or hierarchical scale.
-
D.
usesBodyPart
Indicates that an entity performs an action or function by employing a specific body part as a means or tool.
-
E.
hasBodyRegion
chosen
Indicates that an entity possesses, includes, or is associated with a specific anatomical or bodily region.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:34 p.m.