Triple
T7198692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marsiliana tablet |
E168679
|
entity |
| Predicate | relevanceToField |
P6979
|
FINISHED |
| Object | Etruscology |
—
|
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: Etruscology | Statement: [Marsiliana tablet, relevanceToField, Etruscology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relevanceToField Context triple: [Marsiliana tablet, relevanceToField, Etruscology]
-
A.
relatedField
chosen
Indicates that one field, topic, or area of study is connected or relevant to another in subject matter or application.
-
B.
hasCanonicalRelevance
Indicates that something is considered standard, authoritative, or centrally important within an established canon or reference framework.
-
C.
fieldWithin
Indicates that one field or area is spatially contained entirely within the boundaries of another field or area.
-
D.
relatedTo
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
includesMatch
Indicates that one entity contains or encompasses a particular match or matching instance of another 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_69c68a5376748190bb500f03df86e93e |
completed | March 27, 2026, 1:46 p.m. |
| NER | Named-entity recognition | batch_69c6e92b8bc08190bfcdd34ce42e3448 |
completed | March 27, 2026, 8:31 p.m. |
| PD | Predicate disambiguation | batch_69c6e757fed4819091b0a096e3befc3a |
completed | March 27, 2026, 8:23 p.m. |
Created at: March 27, 2026, 2:52 p.m.