Triple
T29017349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nildoror |
E737351
|
entity |
| Predicate | hasBodyPlanSimilarityTo |
P94757
|
FINISHED |
| Object | elephants |
—
|
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: elephants | Statement: [Nildoror, hasBodyPlanSimilarityTo, elephants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBodyPlanSimilarityTo Context triple: [Nildoror, hasBodyPlanSimilarityTo, elephants]
-
A.
hasBodyPlanType
Indicates that an organism possesses a particular overall structural or morphological body plan type.
-
B.
hasBodyPlanFeature
Indicates that an organism’s body plan includes a specific structural or morphological feature.
-
C.
hasSimilarityTo
chosen
Indicates that one entity shares common characteristics, features, or qualities with another entity to a notable degree.
-
D.
namedForSimilarityTo
Indicates that one entity is given its name because of a perceived resemblance or likeness to another entity.
-
E.
floorPlanSimilarTo
Indicates that one entity has a floor plan that is similar in layout or structure to that 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_69f077ee19f881909af48f9cab00a2e5 |
completed | April 28, 2026, 9:03 a.m. |
| NER | Named-entity recognition | batch_69f7a225a77c81908f8953ccfeb14336 |
completed | May 3, 2026, 7:29 p.m. |
| PD | Predicate disambiguation | batch_69f7a06d4f108190bae3ab9ae431d2c7 |
completed | May 3, 2026, 7:22 p.m. |
Created at: April 28, 2026, 9:46 a.m.