Triple
T38585215
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Patch 2.1 – Black Temple |
E932330
|
entity |
| Predicate | introducedProfessionChanges |
P191755
|
FINISHED |
| Object | Crafting recipe updates |
—
|
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: Crafting recipe updates | Statement: [Patch 2.1 – Black Temple, introducedProfessionChanges, Crafting recipe updates]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: introducedProfessionChanges Context triple: [Patch 2.1 – Black Temple, introducedProfessionChanges, Crafting recipe updates]
-
A.
addedProfessionChanges
chosen
Indicates that one entity has introduced or recorded modifications to another entity’s professional roles or occupations.
-
B.
occupationalChange
Indicates a change in a person’s job, profession, or occupational status over time.
-
C.
includesProfession
Indicates that one entity’s set of attributes, roles, or members contains a specific profession as part of it.
-
D.
introducedProfessionalService
Indicates that one party has presented or connected another party to a professional service or service provider.
-
E.
changedProfessionalNameFrom
Indicates that an entity has altered its professional or working name from a specified previous name.
- 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_69f76ec654d48190b421111cf26e54d9 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69ff2eb19ad88190915fbbe08e8bc84e |
completed | May 9, 2026, 12:55 p.m. |
| PD | Predicate disambiguation | batch_69ff2db5dd608190b7b7ba95f19c276c |
completed | May 9, 2026, 12:51 p.m. |
Created at: May 3, 2026, 4:32 p.m.