Triple
T37461384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mire Keeper |
E930924
|
entity |
| Predicate | belongsToYear |
P75923
|
FINISHED |
| Object | Year of the Kraken |
—
|
NE NERFINISHED |
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: Year of the Kraken | Statement: [Mire Keeper, belongsToYear, Year of the Kraken]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: belongsToYear Context triple: [Mire Keeper, belongsToYear, Year of the Kraken]
-
A.
hasAssociatedYear
chosen
Indicates that an entity is linked to a specific year that is relevant to it (e.g., creation, occurrence, or reference year).
-
B.
associatedClassYear
Indicates a relationship linking an entity to the specific academic class year with which it is connected or identified.
-
C.
relatedYear
Indicates a connection between an entity and a specific year that is relevant to its occurrence, validity, or significance.
-
D.
hasPartInYear
Indicates that something includes or contains a specific part, component, or segment that is associated with a particular year.
-
E.
hasTypeOfYear
Indicates that a given year is classified as belonging to a specific type or category of year (e.g., fiscal, academic, leap).
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a001adc8c108190ab3a43f6415e2be3 |
completed | May 10, 2026, 5:42 a.m. |
| PD | Predicate disambiguation | batch_6a001a290330819097c2c3123f9014b4 |
completed | May 10, 2026, 5:39 a.m. |
Created at: May 3, 2026, 4:17 p.m.