Triple
T5398579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Darlington Hall |
E120716
|
entity |
| Predicate | symbolizesForProtagonist |
P129
|
FINISHED |
| Object | ideal of professional dignity |
—
|
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: ideal of professional dignity | Statement: [Darlington Hall, symbolizesForProtagonist, ideal of professional dignity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: symbolizesForProtagonist Context triple: [Darlington Hall, symbolizesForProtagonist, ideal of professional dignity]
-
A.
symbolizes
chosen
Indicates that one entity stands for, represents, or is used as a sign for another entity, concept, or idea.
-
B.
protagonistIs
Indicates that one entity serves as the main character or central figure in relation to another entity or narrative context.
-
C.
protagonistAlterEgoOf
Indicates that one entity is the alternate identity or secret persona of the main character (protagonist) in a narrative.
-
D.
protagonistCharacteristic
Indicates that a characteristic, trait, or defining quality is attributed to the protagonist in a narrative or scenario.
-
E.
protagonistType
Indicates the role or category that the main character (protagonist) of a story or scenario belongs to.
- 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_69bd4637b92c8190b815b6443ae4b323 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8932b8bc8190bd31e11b167a7212 |
completed | March 20, 2026, 5:51 p.m. |
| PD | Predicate disambiguation | batch_69bd84660ea08190a641084814fcf94d |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.