Triple
T7224630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord of Memphis |
E150347
|
entity |
| Predicate | appliedToDeityRole |
P71453
|
FINISHED |
| Object | patron god of Memphis |
—
|
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: patron god of Memphis | Statement: [Lord of Memphis, appliedToDeityRole, patron god of Memphis]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliedToDeityRole Context triple: [Lord of Memphis, appliedToDeityRole, patron god of Memphis]
-
A.
appliesToDeityIn
chosen
Indicates that something (such as a rule, attribute, or statement) is relevant or applicable to a deity within a specified context or domain.
-
B.
representsDeity
Indicates that one entity serves as a symbolic, artistic, or conceptual depiction of a deity associated with another entity.
-
C.
hasDeityAspect
Indicates that one entity embodies, represents, or functions as a specific divine aspect or manifestation of another deity.
-
D.
hasDeity
Indicates that one entity recognizes, worships, or is associated with another entity as its deity or divine figure.
-
E.
involvesDeity
Indicates that the situation, event, or concept has the participation, presence, or relevance of a deity as a central element of the relationship.
- 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_69c687effb44819092b95d07d0368c9f |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c6e9db51888190b8463d0003f334fa |
completed | March 27, 2026, 8:34 p.m. |
| PD | Predicate disambiguation | batch_69c6e761b7fc8190857794d78af1b468 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:54 p.m.