Triple
T26870812
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harry Markopolos |
E676604
|
entity |
| Predicate | firstMadoffAnalysisYear |
P197919
|
FINISHED |
| Object | 1999 |
—
|
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: 1999 | Statement: [Harry Markopolos, firstMadoffAnalysisYear, 1999]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMadoffAnalysisYear Context triple: [Harry Markopolos, firstMadoffAnalysisYear, 1999]
-
A.
firstReportedYear
Indicates the year in which something was initially reported, documented, or made known for the first time.
-
B.
firstAssumedYear
Indicates the year in which something is initially presumed or taken to have begun, occurred, or become valid.
-
C.
firstSolutionRecognizedYear
Indicates the year in which the first known or accepted solution to a given problem or question was formally recognized.
-
D.
firstReviewYear
Indicates the calendar year in which an entity received its first review.
-
E.
firstSolutionYear
Indicates the year in which the first solution to a given problem, task, or case was achieved or recorded.
- 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_69eee9ba94bc8190b44c5d4397d04ecd |
completed | April 27, 2026, 4:44 a.m. |
| NER | Named-entity recognition | batch_69feba0f09508190b3e871c62b19ec7f |
completed | May 9, 2026, 4:37 a.m. |
| PD | Predicate disambiguation | batch_69feb957fe7c8190969fb31a6d1a59c8 |
completed | May 9, 2026, 4:34 a.m. |
| PDg | Predicate description generation | batch_69feba0e362c81909883a3f24a4a9545 |
completed | May 9, 2026, 4:37 a.m. |
Created at: April 27, 2026, 5:32 a.m.