Triple
T21431619
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mother! |
E528697
|
entity |
| Predicate | hasMetaphoricalElements |
P114548
|
FINISHED |
| Object | Biblical allegory |
—
|
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: Biblical allegory | Statement: [mother!, hasMetaphoricalElements, Biblical allegory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMetaphoricalElements Context triple: [mother!, hasMetaphoricalElements, Biblical allegory]
-
A.
hasMetaphoricalContent
chosen
Indicates that something contains or expresses meaning through metaphorical, rather than purely literal, content.
-
B.
hasMetaphoricalForm
Indicates that one entity is expressed, represented, or understood through a metaphorical form or figurative expression involving another entity.
-
C.
figurativeMeaning
Indicates that one entity is used in a non-literal, metaphorical, or symbolic sense to convey a meaning about another entity or concept.
-
D.
usesScientificMetaphor
Indicates that one entity employs scientific concepts or terminology metaphorically to describe or explain another entity or situation.
-
E.
hasLiteralMeaning
Indicates that one entity expresses the direct, explicit meaning or sense of another entity (such as a word, phrase, or symbol).
- 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_69e0c455f3688190810bc96365791b0f |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e8b3ec70f08190b84c4f747cfb290f |
completed | April 22, 2026, 11:41 a.m. |
| PD | Predicate disambiguation | batch_69e61639ee288190889ffd500d1260f6 |
completed | April 20, 2026, 12:04 p.m. |
Created at: April 16, 2026, 5:49 p.m.