Triple
T5453022
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ram |
E122411
|
entity |
| Predicate | hasHypernym |
P21666
|
FINISHED |
| Object | mammal |
—
|
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: mammal | Statement: [Ram, hasHypernym, mammal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHypernym Context triple: [Ram, hasHypernym, mammal]
-
A.
hasRootWord
Indicates that one linguistic form is derived from, based on, or directly associated with a specified root word.
-
B.
hasSubConcept
chosen
Indicates that one concept is a more specific, subordinate, or narrower idea within the scope of another, more general concept.
-
C.
hasSynapomorphy
Indicates that two or more taxa share a derived character state inherited from their most recent common ancestor, distinguishing that clade from others.
-
D.
hasStem
Indicates that one entity possesses or is characterized by a stem as a structural or functional part.
-
E.
hasCognate
Indicates that two linguistic forms in different languages share a common historical origin, typically descending from the same ancestral word.
- 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_69bd46424248819085282ddf50a565f3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd95be329c81908783420cf81b6af5 |
completed | March 20, 2026, 6:45 p.m. |
| PD | Predicate disambiguation | batch_69bd919e8d18819098c4af6a015e5cc2 |
completed | March 20, 2026, 6:27 p.m. |
Created at: March 20, 2026, 2:08 p.m.