Triple
T14481412
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | cult of Ramesses II |
E359109
|
entity |
| Predicate | portraysSubjectAs |
P100368
|
FINISHED |
| Object | living god |
—
|
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: living god | Statement: [cult of Ramesses II, portraysSubjectAs, living god]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portraysSubjectAs Context triple: [cult of Ramesses II, portraysSubjectAs, living god]
-
A.
portraysPersonAs
chosen
Indicates that one entity represents, depicts, or characterizes another person in a particular way or role.
-
B.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
C.
portrayedAsFrom
Indicates that one entity is depicted or represented as originating from, or belonging to, the place or source specified by another entity.
-
D.
depictedSubject
Indicates that one entity visually represents or portrays another entity as its subject in an image or depiction.
-
E.
portrayalIntendedAs
Indicates that one entity is meant to represent, depict, or stand in for another entity in an intentional portrayal.
- 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_69d827966698819082e140837737501d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924bc548819087a2f693840d7426 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.