Triple
T34791818
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Contes de ma mère l’Oye |
E1002967
|
entity |
| Predicate | hasMoralizingElements |
P57332
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Les Contes de ma mère l’Oye, hasMoralizingElements, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralizingElements Context triple: [Les Contes de ma mère l’Oye, hasMoralizingElements, true]
-
A.
hasMoralizingFunction
Indicates that something serves to convey, reinforce, or promote moral norms, values, or judgments within a context or interaction.
-
B.
hasMoralMessage
chosen
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
-
C.
hasMoralFraming
Indicates that something is presented or interpreted in terms of moral values, judgments, or ethical considerations.
-
D.
hasMoralCharacteristic
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
E.
hasMoralPerspective
Indicates that an entity holds or applies a particular moral or ethical viewpoint in evaluating actions, situations, or other entities.
- 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_69f76db47d408190a24fc7164439ea2d |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fee25dbca481909e6f1c255122b3a8 |
completed | May 9, 2026, 7:29 a.m. |
| PD | Predicate disambiguation | batch_69fee1c8915c8190b08b63e42881f1a9 |
completed | May 9, 2026, 7:27 a.m. |
Created at: May 3, 2026, 3:59 p.m.