Triple
T22813551
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Υ(4S) |
E565043
|
entity |
| Predicate | hasJPCC |
P149823
|
FINISHED |
| Object | 1^{--} |
—
|
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: 1^{--} | Statement: [Υ(4S), hasJPCC, 1^{--}]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasJPCC
Context triple: [Υ(4S), hasJPCC, 1^{--}]
-
A.
hasPP
Indicates that an entity is associated with a particular prepositional phrase (PP) that modifies or relates to it in a syntactic or semantic structure.
-
B.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
-
C.
hasJCR
Indicates that one entity possesses, is associated with, or is linked to a specific JCR (Journal Citation Reports) value, record, or classification.
-
D.
hasJet
Indicates that an entity possesses, operates, or is equipped with a jet aircraft.
-
E.
hasMP
Indicates that an entity is represented by, or associated with, a specific Member of Parliament (MP).
- 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17d61c6f081908d3911710b3aff51 |
completed | April 29, 2026, 3:39 a.m. |
| PD | Predicate disambiguation | batch_69eed2cb30f481909566369f515f6eff |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb5681f88190821129ced752f190 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:32 p.m.