Triple
T36524744
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agent Champagne |
E900269
|
entity |
| Predicate | hasCodenameTheme |
P68530
|
FINISHED |
| Object | alcoholic beverages |
—
|
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: alcoholic beverages | Statement: [Agent Champagne, hasCodenameTheme, alcoholic beverages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCodenameTheme Context triple: [Agent Champagne, hasCodenameTheme, alcoholic beverages]
-
A.
usesCodenameTheme
chosen
Indicates that an entity adopts a consistent codename pattern or motif (e.g., colors, planets, mythological figures) for naming related items or agents.
-
B.
hasCodenameSeries
Indicates that an entity is associated with, or belongs to, a particular codename-based series.
-
C.
hasCodenameLanguage
Indicates that a codename is expressed or defined in a particular language.
-
D.
relatedCodename
Indicates that one entity has an associated or connected codename that is contextually related to it.
-
E.
hasNicknameTheme
Indicates that an entity’s nickname is based on or associated with a particular theme or motif.
- 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_69f76e5eedb88190a393b8c623f71dd7 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_6a037c8e2c648190a65fc9c7872861af |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a0bf4b88190bdcfae9a14b51f0a |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:11 p.m.