Triple
T5516366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cestoda |
E144692
|
entity |
| Predicate | hasAttachmentOrgan |
P65198
|
FINISHED |
| Object | suckers |
—
|
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: suckers | Statement: [Cestoda, hasAttachmentOrgan, suckers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAttachmentOrgan Context triple: [Cestoda, hasAttachmentOrgan, suckers]
-
A.
hasOrganSystem
Indicates that an entity possesses or is associated with a particular organ system as part of its biological structure or function.
-
B.
hasTissue
Indicates that one entity possesses, contains, or is associated with a specific tissue of another entity.
-
C.
hadOrgan
Indicates that an entity previously possessed or contained a specific organ as part of its body.
-
D.
hasMainOrgan
Indicates that an entity possesses a primary or principal organ that plays a central role in its biological or functional system.
-
E.
associatedBody
Indicates a relationship where one entity is linked or connected to another entity as its related or corresponding body.
- 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_69c008f77ff88190b0cd50ca207295d1 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f5e8ce08190b7f5f2131bebcd4f |
completed | March 22, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69c01b0a06348190b39ac9fe80d2836a |
completed | March 22, 2026, 4:38 p.m. |
| PDg | Predicate description generation | batch_69c01f051e508190b3886d87b4afdd0b |
completed | March 22, 2026, 4:55 p.m. |
Created at: March 22, 2026, 3:33 p.m.