Triple
T38645348
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sun King’s Salvation |
E938699
|
entity |
| Predicate | encounterID |
P191651
|
FINISHED |
| Object | 2398 |
—
|
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: 2398 | Statement: [Sun King’s Salvation, encounterID, 2398]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encounterID Context triple: [Sun King’s Salvation, encounterID, 2398]
-
A.
encounterOrder
Indicates the sequence in which entities meet or come into contact with each other.
-
B.
hasEncounter
Indicates that one entity experiences or comes into contact with another entity or event, typically in a specific context or situation.
-
C.
encounterLocation
Indicates the place or setting where two or more entities meet, interact, or come into contact.
-
D.
encounterStructure
Indicates a relationship where an entity comes into contact with or experiences a particular structure or constructed arrangement.
-
E.
encounterStyle
Indicates the manner or format in which two or more entities meet, interact, or come into contact with each other.
- F. None of above. chosen
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_69f76ed948ec81908ce7811608a8f359 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fce545fec881909247a3af821d21ae |
completed | May 7, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_69fce12eaeec81908cf81346b2cef6e0 |
completed | May 7, 2026, 6:59 p.m. |
| PDg | Predicate description generation | batch_69fce54532948190a5cfacfe18e09322 |
completed | May 7, 2026, 7:17 p.m. |
Created at: May 3, 2026, 4:32 p.m.