Triple
T27208738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cercopithecoidea |
E683941
|
entity |
| Predicate | hasDentalFormula |
P35359
|
FINISHED |
| Object | 2.1.2.3 upper and lower jaw dental formula |
—
|
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: 2.1.2.3 upper and lower jaw dental formula | Statement: [Cercopithecoidea, hasDentalFormula, 2.1.2.3 upper and lower jaw dental formula]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDentalFormula Context triple: [Cercopithecoidea, hasDentalFormula, 2.1.2.3 upper and lower jaw dental formula]
-
A.
hasTeeth
Indicates that one entity possesses teeth as a physical feature.
-
B.
hasTeethCount
Indicates the specific number of teeth possessed by an entity.
-
C.
hasTeethAdaptedFor
Indicates that an organism’s teeth are specially shaped or structured to suit a particular function, diet, or environmental condition.
-
D.
distinguishingDentalFeature
Indicates that one entity has a dental characteristic that serves to differentiate it from another entity or group.
-
E.
dentition
chosen
Indicates the type, arrangement, or condition of teeth that an entity possesses.
- 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_69eefad339a08190aeacb2a198f1a39b |
completed | April 27, 2026, 5:57 a.m. |
| NER | Named-entity recognition | batch_69f7516d5b4081908588a6feb541f355 |
completed | May 3, 2026, 1:45 p.m. |
| PD | Predicate disambiguation | batch_69f74d40ebb081909daf60623e38f41d |
completed | May 3, 2026, 1:27 p.m. |
Created at: April 27, 2026, 9:38 a.m.