Triple
T11020706
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Statesman |
E260479
|
entity |
| Predicate | memberCodenamesBasedOn |
P96617
|
FINISHED |
| Object | American alcoholic drinks |
—
|
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: American alcoholic drinks | Statement: [Statesman, memberCodenamesBasedOn, American alcoholic drinks]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: memberCodenamesBasedOn Context triple: [Statesman, memberCodenamesBasedOn, American alcoholic drinks]
-
A.
codenameByOpponents
Indicates that opponents assign or use a particular codename for the referenced entity.
-
B.
nameLiterallyMeans
Indicates that the literal meaning or direct translation of one entity’s name is given by the other entity.
-
C.
nameAllusion
Indicates that one entity’s name is derived from, references, or alludes to another entity.
-
D.
codenameColor
Indicates that an entity’s codename is associated with or represented by a specific color.
-
E.
codenameUser
Indicates that a user is assigned or associated with a particular codename.
- 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_69d6aa9687448190b28d353b1b6a610e |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797baad408190a53fd6941a750f68 |
completed | April 9, 2026, 12:12 p.m. |
| PD | Predicate disambiguation | batch_69d72e995e008190bbffb314129ed0cd |
completed | April 9, 2026, 4:44 a.m. |
| PDg | Predicate description generation | batch_69d732242fdc8190be77d1f730a42935 |
completed | April 9, 2026, 4:59 a.m. |
Created at: April 8, 2026, 9:25 p.m.