Triple
T37198005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lados |
E921645
|
entity |
| Predicate | relatedToMotive |
P205777
|
FINISHED |
| Object | quest for the golden apples |
—
|
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: quest for the golden apples | Statement: [Lados, relatedToMotive, quest for the golden apples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedToMotive Context triple: [Lados, relatedToMotive, quest for the golden apples]
-
A.
hasMotiveOfCriminals
Indicates that the specified motive is attributed to or associated with the criminals in question.
-
B.
relatedBelief
Indicates that one belief is connected to, derived from, or otherwise associated with another belief in some meaningful way.
-
C.
depictsMotive
Indicates that one entity visually represents or illustrates the motive, intention, or underlying reason associated with another entity or action.
-
D.
mayRelateTo
Indicates a possible, but not certain, relationship or association between two entities.
-
E.
moreCloselyRelatedTo
Indicates that one entity has a stronger or closer relationship, connection, or similarity to a second entity than to some other reference 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_69f76ea313a08190a54404cd1e47da90 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:15 p.m.