Triple
T28626986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kingu |
E724550
|
entity |
| Predicate | associatedTextualMotif |
P8272
|
FINISHED |
| Object | Tablet of Destinies |
E1824038
|
NE 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: Tablet of Destinies | Statement: [Kingu, associatedTextualMotif, Tablet of Destinies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedTextualMotif Context triple: [Kingu, associatedTextualMotif, Tablet of Destinies]
-
A.
featuresMotif
Indicates that something contains, incorporates, or prominently includes a particular recurring motif or pattern.
-
B.
usesMotifsFrom
Indicates that one entity incorporates or draws upon recurring themes, patterns, or elements that originate from another entity.
-
C.
associatedWithText
chosen
Indicates that an entity has a contextual or semantic connection to a specific piece of text.
-
D.
transformationMotif
Indicates a recurring pattern or theme in which one entity undergoes a change in form, state, or identity in relation to another.
-
E.
primaryMotif
Indicates that one entity serves as the main recurring theme or dominant motif associated with another entity.
- F. None of above.
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_69f01d822ac08190932de59ec2268ed2 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_6a01a0b63d148190b10206509c0a0a5b |
completed | May 11, 2026, 9:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1ccf36a3408190a045b1488041a7d3 |
completed | June 1, 2026, 12:15 a.m. |
| PD | Predicate disambiguation | batch_6a01a0245d4c8190a3c3fbbe83f0389d |
completed | May 11, 2026, 9:23 a.m. |
Created at: April 28, 2026, 4:36 a.m.