Triple
T35561432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | sanctuary of Endymion |
E1027644
|
entity |
| Predicate | hasAssociatedMotif |
P41002
|
FINISHED |
| Object | eternal sleep of Endymion |
—
|
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: eternal sleep of Endymion | Statement: [sanctuary of Endymion, hasAssociatedMotif, eternal sleep of Endymion]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAssociatedMotif Context triple: [sanctuary of Endymion, hasAssociatedMotif, eternal sleep of Endymion]
-
A.
hasTypeOfMotif
Indicates that one entity features or is characterized by a specific kind or category of motif.
-
B.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
-
C.
hasSignalingMotif
Indicates that one entity contains or exhibits a specific molecular or structural motif involved in signaling processes related to another entity.
-
D.
hasMirrorMotif
Indicates that one entity features a mirror-related motif or pattern in relation to another entity or context.
-
E.
featuresMotif
chosen
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69fd2cf39b0c8190811b8a6fa9410560 |
completed | May 8, 2026, 12:23 a.m. |
| PD | Predicate disambiguation | batch_69fd2ad8dd988190a9899701ba00d917 |
completed | May 8, 2026, 12:14 a.m. |
Created at: May 3, 2026, 4:04 p.m.