Triple
T37291318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philippine Negrito populations |
E925671
|
entity |
| Predicate | notGeneticallyIdenticalTo |
P8167
|
FINISHED |
| Object | African Pygmy populations |
—
|
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: African Pygmy populations | Statement: [Philippine Negrito populations, notGeneticallyIdenticalTo, African Pygmy populations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notGeneticallyIdenticalTo Context triple: [Philippine Negrito populations, notGeneticallyIdenticalTo, African Pygmy populations]
-
A.
geneticallyIdenticalTo
Indicates that two entities share the same genetic makeup, with no differences in their DNA sequence.
-
B.
notGeneticallyRelatedTo
chosen
Indicates that there is no genetic or hereditary relationship between the two entities.
-
C.
hasMorphologyDistinctFrom
Indicates that the morphology (form or structure) of one entity is different from that of another entity.
-
D.
mechanicallyDistinctFrom
Indicates that two entities differ in their mechanical properties, structure, or behavior such that they are not mechanically equivalent or interchangeable.
-
E.
differentiatedFrom
Indicates that one entity is distinguished or set apart from another by identifying differences between them.
- 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_69f76eb0f86c819098dee07393e69ec3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fb78cbef988190b8f79d946b46e6b2 |
completed | May 6, 2026, 5:22 p.m. |
| PD | Predicate disambiguation | batch_69fb5a9ac5a08190b24ef308963fc52b |
completed | May 6, 2026, 3:13 p.m. |
Created at: May 3, 2026, 4:16 p.m.