Triple
T18301861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FRSAD |
E438375
|
entity |
| Predicate | themaDefinition |
P81245
|
FINISHED |
| Object | any entity used as the subject of a work |
—
|
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: any entity used as the subject of a work | Statement: [FRSAD, themaDefinition, any entity used as the subject of a work]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: themaDefinition Context triple: [FRSAD, themaDefinition, any entity used as the subject of a work]
-
A.
wordDefinition
Indicates that one entity provides the meaning or explanation of a word represented by the other entity.
-
B.
thematicConcept
chosen
Indicates that one entity embodies, expresses, or is centrally concerned with a particular underlying theme or conceptual idea represented by the other entity.
-
C.
theme
Indicates the entity that is the primary participant or content affected or characterized by an action, event, or state.
-
D.
duMeaning
Indicates that one entity expresses, conveys, or signifies a particular meaning or sense in relation to another.
-
E.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50180ac48819090e9a8f11ba10c3d |
completed | April 19, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.