Triple
T20469752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Judge Tyrone Kipler |
E502156
|
entity |
| Predicate | basedOnWorkPublicationDecade |
P140203
|
FINISHED |
| Object | 1990s |
—
|
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: 1990s | Statement: [Judge Tyrone Kipler, basedOnWorkPublicationDecade, 1990s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: basedOnWorkPublicationDecade Context triple: [Judge Tyrone Kipler, basedOnWorkPublicationDecade, 1990s]
-
A.
firstWorkPublicationDecade
Indicates the decade during which an entity’s first work was published.
-
B.
publicationDecade
Indicates the decade during which a publication was released or made publicly available.
-
C.
hasWorkPublicationCentury
Indicates the century during which a given work was published.
-
D.
basedOnWorkAppearedIn
Indicates that something is derived from, adapted from, or otherwise created using a work that appeared in a specified source or publication.
-
E.
firstWorkPublicationCentury
Indicates the century in which an entity’s first work was originally published.
- 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_69e0b4ae5f1081908768b0c9a3a0bf38 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6995f753081909bbe03f7c251d9c1 |
completed | April 20, 2026, 9:23 p.m. |
| PD | Predicate disambiguation | batch_69e57679eb40819086142df3e39c928e |
completed | April 20, 2026, 12:42 a.m. |
| PDg | Predicate description generation | batch_69e58d766b408190a1d3698145fb6d30 |
completed | April 20, 2026, 2:20 a.m. |
Created at: April 16, 2026, 11:33 a.m.