Triple
T16964712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Global Forest Resources Assessment |
E411512
|
entity |
| Predicate | firstGlobalAssessmentYear |
P125405
|
FINISHED |
| Object | 1990 |
—
|
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: 1990 | Statement: [Global Forest Resources Assessment, firstGlobalAssessmentYear, 1990]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstGlobalAssessmentYear Context triple: [Global Forest Resources Assessment, firstGlobalAssessmentYear, 1990]
-
A.
firstScreeningYear
Indicates the year in which an entity (such as a film or show) was first publicly screened or premiered.
-
B.
firstReviewYear
Indicates the calendar year in which an entity received its first review.
-
C.
firstAssumedYear
Indicates the year in which something is initially presumed or taken to have begun, occurred, or become valid.
-
D.
firstPlanStartYear
Indicates the calendar year in which an entity’s initial plan or planning period begins.
-
E.
firstTrialYear
Indicates the year in which an entity’s first trial or initial formal testing took place.
- 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_69d886c9c9d481909afe222093641cae |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d0a2cda88190bd574a869f0e43e9 |
completed | April 18, 2026, 6:42 p.m. |
| PD | Predicate disambiguation | batch_69e32b9cddf88190bc42709604047353 |
completed | April 18, 2026, 6:58 a.m. |
| PDg | Predicate description generation | batch_69e355722040819098830dabf207ecd6 |
completed | April 18, 2026, 9:57 a.m. |
Created at: April 10, 2026, 5:31 a.m.