Triple
T34376661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mibsam |
E882302
|
entity |
| Predicate | textualSignificance |
P134238
|
FINISHED |
| Object | minor character |
—
|
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: minor character | Statement: [Mibsam, textualSignificance, minor character]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: textualSignificance Context triple: [Mibsam, textualSignificance, minor character]
-
A.
linguisticSignificance
Indicates the degree to which something is important, influential, or meaningful within a particular language or linguistic system.
-
B.
textualCharacterization
chosen
Indicates that one entity provides a descriptive or narrative characterization of another entity, typically in textual form.
-
C.
stylisticSignificance
Indicates that one entity holds importance or meaning specifically because of its style or manner of expression in relation to another entity or context.
-
D.
textMeaning
Indicates that one text expresses, conveys, or corresponds to a particular meaning or semantic content.
-
E.
logicalMeaning
Indicates that one entity expresses, encodes, or conveys the logical content, implication, or formal meaning of another.
- 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_69f349bf5d7481908dd5da4cbdf74047 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:59 a.m.