Triple
T8821637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Justice |
E209917
|
entity |
| Predicate | blindfoldRepresents |
P84820
|
FINISHED |
| Object | impartiality |
—
|
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: impartiality | Statement: [Lady Justice, blindfoldRepresents, impartiality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: blindfoldRepresents Context triple: [Lady Justice, blindfoldRepresents, impartiality]
-
A.
blindedBy
Indicates that one entity causes another to lose the ability to see or perceive clearly, either literally or metaphorically.
-
B.
blinded
Indicates that one entity causes another to lose the ability to see, either temporarily or permanently.
-
C.
visionOrSign
Indicates a relationship where something is perceived or presented as a vision, sign, or symbolic manifestation, often conveying a message, omen, or divine indication.
-
D.
blueRepresents
Indicates that the color blue is used to symbolize, denote, or stand for a particular concept, state, or category in a given context.
-
E.
containsVisionOf
Indicates that one entity includes, depicts, or embodies a visual representation or image of another entity.
- F. None of above. chosen
Provenance (4 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc601126248190b6f10c22f1aeac9a |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
| PDg | Predicate description generation | batch_69cc5cff3608819081d2d7e5c16d44b7 |
completed | March 31, 2026, 11:47 p.m. |
Created at: March 30, 2026, 6:46 p.m.