Triple
T16267702
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sipuncula |
E394914
|
entity |
| Predicate | hasBodyWall |
P48124
|
FINISHED |
| Object | circular and longitudinal muscles |
—
|
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 | Statement: [Sipuncula, hasBodyWall, circular and longitudinal muscles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyWall Context triple: [Sipuncula, hasBodyWall, circular and longitudinal muscles]
-
A.
hasBodyCavity
Indicates that an organism possesses an internal body cavity or space within its body structure.
-
B.
hasBodyPlanFeature
chosen
Indicates that an organism’s body plan includes a specific structural or morphological feature.
-
C.
hasBodyUnit
Indicates that something possesses or is associated with a specific physical unit or component of a body.
-
D.
hasSurfaceBody
Indicates that one entity possesses or is characterized by a particular surface or outer body.
-
E.
hasBodyOf
Indicates that one entity possesses, contains, or is composed of the physical body or main substance of another entity.
- 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_69d87f221d8081909b0b2063e7528ba2 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e245c963ec8190b059fecac6248cd9 |
completed | April 17, 2026, 2:38 p.m. |
| PD | Predicate disambiguation | batch_69e219f259e88190bf49d8408c04178e |
completed | April 17, 2026, 11:30 a.m. |
Created at: April 10, 2026, 5:05 a.m.