Triple
T144716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Field Museum of Natural History |
E2928
|
entity |
| Predicate | hasResearchDepartment |
P589
|
FINISHED |
| Object | Anthropology |
—
|
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: Anthropology | Statement: [Field Museum of Natural History, hasResearchDepartment, Anthropology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResearchDepartment Context triple: [Field Museum of Natural History, hasResearchDepartment, Anthropology]
-
A.
hasResearchArea
Indicates that an entity (such as a person, project, or organization) is associated with or focused on a particular field or area of research.
-
B.
containsResearchStation
Indicates that one entity geographically includes or hosts a research station within its boundaries.
-
C.
hasAcademicDepartment
chosen
Indicates that an institution or organization includes or is associated with a specific academic department.
-
D.
departmentType
Indicates the classification or category of a department, specifying what kind of department it is.
-
E.
department
Indicates that one entity functions as an organizational unit or division within another, typically larger, entity.
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257e935bc8190a03e54a10e9ba6f7 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a25656a4fc81908a87678ac3d28f93 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.