Triple
T3322016
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kerch Historical and Archaeological Museum |
E69815
|
entity |
| Predicate | hasThematicArea |
P28568
|
FINISHED |
| Object | ancient Greek colonies in Crimea |
—
|
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: ancient Greek colonies in Crimea | Statement: [Kerch Historical and Archaeological Museum, hasThematicArea, ancient Greek colonies in Crimea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasThematicArea Context triple: [Kerch Historical and Archaeological Museum, hasThematicArea, ancient Greek colonies in Crimea]
-
A.
thematicArea
chosen
Indicates the subject or item is associated with, or falls under, a particular thematic area or topic of focus.
-
B.
containsThemeArea
Indicates that one entity includes or encompasses a specific thematic area as part of its scope or content.
-
C.
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.
-
D.
hasPolicyArea
Indicates that an entity (such as a policy, program, or initiative) is associated with or pertains to a specific policy area or domain.
-
E.
isPartOfPolicyArea
Indicates that one policy, topic, or issue belongs to, falls under, or is categorized within a broader policy area or domain.
- 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_69ad85a1829881908942c14075644d0d |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb13d13a88190828d9a03fd0865ce |
completed | March 8, 2026, 5:26 p.m. |
| PD | Predicate disambiguation | batch_69ada42a19348190a3862ce02451f4aa |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:11 p.m.