Triple
T37460223
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patchwerk |
E930898
|
entity |
| Predicate | encounterDesign |
P189394
|
FINISHED |
| Object | tank and healer check |
—
|
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: tank and healer check | Statement: [Patchwerk, encounterDesign, tank and healer check]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: encounterDesign Context triple: [Patchwerk, encounterDesign, tank and healer check]
-
A.
settingEncounter
Indicates that an encounter or interaction is taking place within a particular setting or environment.
-
B.
encounterStyle
Indicates the manner or format in which two or more entities meet, interact, or come into contact with each other.
-
C.
encountered
Indicates that one entity came across or met another entity, typically in a specific place or context, often unexpectedly or during the course of some activity.
-
D.
encountersCharacter
Indicates that one character comes into contact with or meets another character, typically within a particular situation or context.
-
E.
designedAttraction
Indicates that one entity intentionally created or planned another entity to be appealing or attractive to a target audience or observer.
- 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_69f76ec1a1148190b0a961f188d621b0 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbbc49da8c8190902bbb05d2477cab |
completed | May 6, 2026, 10:10 p.m. |
| PD | Predicate disambiguation | batch_69fbb13f34b08190bbbb220ac1e6e666 |
completed | May 6, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69fbbc48b75c8190bec27dd4b7de797f |
completed | May 6, 2026, 10:10 p.m. |
Created at: May 3, 2026, 4:17 p.m.