Triple
T784265
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Annelida |
E16565
|
entity |
| Predicate | musculature |
P19589
|
FINISHED |
| Object | circular and longitudinal muscles in body wall |
—
|
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: circular and longitudinal muscles in body wall | Statement: [Annelida, musculature, circular and longitudinal muscles in body wall]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: musculature Context triple: [Annelida, musculature, circular and longitudinal muscles in body wall]
-
A.
limbType
Indicates the specific kind or category of limb associated with an entity (e.g., arm, leg, wing, fin).
-
B.
strength
Indicates the degree of power, intensity, or effectiveness with which an entity can act on, influence, or withstand another entity or force.
-
C.
locomotion
Indicates movement or the ability to move from one place to another.
-
D.
hasLimbs
Indicates that an entity possesses one or more limbs as physical appendages.
-
E.
strengthPeak
Indicates the point or period at which an entity’s strength reaches its maximum level.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a769dc6481908f12e872f997acf3 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a50db97c8190a1c55673f4a357b4 |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a67e69288190b3dc278c5bd94155 |
completed | March 1, 2026, 8:50 p.m. |
Created at: March 1, 2026, 7:37 p.m.