Triple
T29838549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Getting Here: The Story of Human Evolution |
E757719
|
entity |
| Predicate | hasAuthorExpertiseIn |
P466
|
FINISHED |
| Object | human skeletal biology |
—
|
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: human skeletal biology | Statement: [Getting Here: The Story of Human Evolution, hasAuthorExpertiseIn, human skeletal biology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAuthorExpertiseIn Context triple: [Getting Here: The Story of Human Evolution, hasAuthorExpertiseIn, human skeletal biology]
-
A.
basedOnExpertiseOf
Indicates that something is determined, derived, or justified using the knowledge, skills, or judgment of a particular expert or group of experts.
-
B.
hasAuthor
Indicates that an entity is written or created by a specific author.
-
C.
hasAuthorOf
Indicates that one entity is the author or creator of another entity (such as a work, document, or publication).
-
D.
hasSpecialty
chosen
Indicates that an entity possesses a particular area of expertise, focus, or professional specialization.
-
E.
hasSpecialist
Indicates that one entity is associated with or assigned to a specialist entity that provides expert support, service, or oversight for it.
- 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_69f224593f6c81908785a560fe659f58 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f7308a096081909d66a56f3c926806 |
completed | May 3, 2026, 11:24 a.m. |
| PD | Predicate disambiguation | batch_69f72a00c5f081908b6539d15baf4e12 |
completed | May 3, 2026, 10:57 a.m. |
Created at: April 29, 2026, 5:38 p.m.