Triple
T9358431
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | David Swan |
E225209
|
entity |
| Predicate | hasMoralOrLesson |
P57332
|
FINISHED |
| Object | Important opportunities in life may pass unnoticed. |
—
|
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: Important opportunities in life may pass unnoticed. | Statement: [David Swan, hasMoralOrLesson, Important opportunities in life may pass unnoticed.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMoralOrLesson Context triple: [David Swan, hasMoralOrLesson, Important opportunities in life may pass unnoticed.]
-
A.
hasMoralMessage
chosen
Indicates that something conveys or embodies a lesson, value, or guidance about what is right or wrong behavior.
-
B.
hasMoralCharacteristic
Indicates that an entity possesses a particular moral quality, trait, or ethical attribute.
-
C.
hasMoralFunction
Indicates that an entity serves or fulfills a role related to moral or ethical considerations.
-
D.
hasMoralCode
Indicates that an entity adheres to or is guided by a set of moral principles or ethical rules.
-
E.
hasMoralPurpose
Indicates that an entity, action, or decision is guided by or oriented toward ethical values, principles, or morally significant goals.
- 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_69ca842bdd648190904131d58620d448 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd4ff19ab48190a8d85c8ac2644c89 |
completed | April 1, 2026, 5:03 p.m. |
| PD | Predicate disambiguation | batch_69cc7a68ab9481909f97cb70764697cc |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:42 p.m.