Triple
T27271215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homo luzonensis |
E688055
|
entity |
| Predicate | dentalMorphology |
P35359
|
FINISHED |
| Object | small molars |
—
|
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: small molars | Statement: [Homo luzonensis, dentalMorphology, small molars]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dentalMorphology Context triple: [Homo luzonensis, dentalMorphology, small molars]
-
A.
distinguishingDentalFeature
Indicates that one entity has a dental characteristic that serves to differentiate it from another entity or group.
-
B.
dentition
chosen
Indicates the type, arrangement, or condition of teeth that an entity possesses.
-
C.
fossilMorphology
Indicates that one entity describes or characterizes the physical form and structural features of a fossil associated with another entity.
-
D.
skullMorphology
Indicates a relationship where entities are characterized or compared based on the form, structure, or anatomical features of their skulls.
-
E.
toothAdaptation
Indicates how an organism’s teeth are structurally or functionally modified in response to its diet, environment, or evolutionary pressures.
- 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_69ef3558cf8881909595ef89daf6e14a |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69f62cd2ceb481908cd9fae52a542206 |
completed | May 2, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69f62c1762f881908c25e8f70ecd5041 |
completed | May 2, 2026, 4:53 p.m. |
Created at: April 27, 2026, 10:59 a.m.