Triple
T4238108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hera Parthenos |
E94742
|
entity |
| Predicate | hasTheonymType |
P12903
|
FINISHED |
| Object | cultic epithet |
—
|
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: cultic epithet | Statement: [Hera Parthenos, hasTheonymType, cultic epithet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTheonymType Context triple: [Hera Parthenos, hasTheonymType, cultic epithet]
-
A.
hasMythType
Indicates that an entity is associated with or classified under a particular type or category of myth.
-
B.
hasPantheonName
Indicates that an entity is associated with a specific pantheon and is identified by the given pantheon name.
-
C.
hasNicknamedEntityType
Indicates that an entity is associated with another entity type specifically in the role of being its nickname or informal name.
-
D.
hasEndonymType
Indicates the specific type or category of an entity’s endonym (its name in its own language or local usage).
-
E.
hasAppellationType
chosen
Indicates that an entity’s name or title is associated with a specific category or type of appellation.
- 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_69b34537cc6481909cd0a96acbb33ef7 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34e7589b48190a16e7ff29fb6a162 |
completed | March 12, 2026, 11:38 p.m. |
| PD | Predicate disambiguation | batch_69b347f3bd188190b0cd613e8a5c1683 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:05 p.m.