Triple
T4387963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Myriapoda |
E99291
|
entity |
| Predicate | legAttachment |
P50709
|
FINISHED |
| Object | one pair of legs per trunk segment or segment diplosegments |
—
|
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: one pair of legs per trunk segment or segment diplosegments | Statement: [Myriapoda, legAttachment, one pair of legs per trunk segment or segment diplosegments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legAttachment Context triple: [Myriapoda, legAttachment, one pair of legs per trunk segment or segment diplosegments]
-
A.
legCharacteristic
Indicates a characteristic, property, or attribute that specifically pertains to the legs of an entity.
-
B.
legOrientation
Indicates the relative positioning or directional alignment of an entity’s leg(s) with respect to a reference frame or another object.
-
C.
appendages
chosen
Indicates that one entity has limbs or projecting body parts that are attached to another entity.
-
D.
attachedTo
Indicates that one entity is physically or logically fastened, connected, or joined to another entity.
-
E.
legArmorType
Indicates the specific category or kind of protective covering worn on the legs.
- 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_69b3454f739481909ff6c28331f0c0b9 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b352804be88190ab188ac0dde1ac1e |
completed | March 12, 2026, 11:55 p.m. |
| PD | Predicate disambiguation | batch_69b34f572efc8190bad1e5078cbcb75a |
completed | March 12, 2026, 11:42 p.m. |
Created at: March 12, 2026, 11:19 p.m.