Triple
T808340
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arthropoda |
E17486
|
entity |
| Predicate | hasBodyRegion |
P21283
|
FINISHED |
| Object | head |
—
|
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 | Statement: [Arthropoda, hasBodyRegion, head]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyRegion Context triple: [Arthropoda, hasBodyRegion, head]
-
A.
bodyCovering
Indicates the type of external covering or surface (such as skin, fur, feathers, or scales) that characterizes an entity’s body.
-
B.
associatedBody
Indicates a relationship where one entity is linked or connected to another entity as its related or corresponding body.
-
C.
seatOnBody
Indicates that one entity functions as a seat or seating surface that is physically attached or integrated to a body or body-like structure.
-
D.
hasRegion
Indicates that an entity includes, contains, or is associated with a specific geographic or administrative region as part of its scope or structure.
-
E.
hasTissue
Indicates that one entity possesses, contains, or is associated with a specific tissue of another entity.
- 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_69a4937ae8a08190b5084a03d532b30e |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ac07fedc8190ab05595f25c1792f |
completed | March 1, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69a4aa7221c081908068e66fe720f26d |
completed | March 1, 2026, 9:06 p.m. |
| PDg | Predicate description generation | batch_69a4ac0688708190b62ac0a8239ec8c8 |
completed | March 1, 2026, 9:13 p.m. |
Created at: March 1, 2026, 7:38 p.m.