Triple
T31535318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | multiple system atrophy |
E804586
|
entity |
| Predicate | hasFirstDescription |
P197265
|
FINISHED |
| Object | 1960s as Shy–Drager syndrome |
—
|
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: 1960s as Shy–Drager syndrome | Statement: [multiple system atrophy, hasFirstDescription, 1960s as Shy–Drager syndrome]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstDescription Context triple: [multiple system atrophy, hasFirstDescription, 1960s as Shy–Drager syndrome]
-
A.
hasDescription
Indicates that an entity is associated with a textual description that explains or characterizes it.
-
B.
hasFirstTerms
Indicates that one entity includes or is associated with the initial or earliest terms of another entity (such as a sequence, series, or agreement).
-
C.
hasFirstVersion
Indicates that one entity is the earliest or original version in a sequence of versions related to another entity.
-
D.
hasMajorDescription
Indicates that an entity has a textual description specifying or elaborating on its academic major.
-
E.
hasFirstTerm
Indicates that an entity is associated with a specific first term in an ordered sequence, period, or series.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe831c97c88190b27ecf100e25c2a0 |
completed | May 9, 2026, 12:43 a.m. |
| PD | Predicate disambiguation | batch_69fe7f1b92648190b14e56bcaee5d0ca |
completed | May 9, 2026, 12:26 a.m. |
| PDg | Predicate description generation | batch_69fe831ba4708190a5564afd7d5a4319 |
completed | May 9, 2026, 12:43 a.m. |
Created at: April 30, 2026, 10:03 p.m.