Triple
T1865533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Universal Camouflage Pattern |
E34911
|
entity |
| Predicate | fullyReplacedByYear |
P33237
|
FINISHED |
| Object | 2019 |
—
|
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: 2019 | Statement: [Universal Camouflage Pattern, fullyReplacedByYear, 2019]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fullyReplacedByYear Context triple: [Universal Camouflage Pattern, fullyReplacedByYear, 2019]
-
A.
secondHalvingYear
Indicates the calendar year in which the second halving event of a recurring, typically periodic, process or quantity occurs.
-
B.
thirdHalvingYear
Indicates the calendar year in which the third occurrence of a recurring halving event (such as a scheduled reduction in rate or quantity) takes place.
-
C.
firstHalvingYear
Indicates the calendar year in which the first halving event associated with an entity (such as a cryptocurrency’s block reward) occurs.
-
D.
firstRedenominationYear
Indicates the year in which a currency or financial unit was first redenominated (i.e., its face value was officially recalibrated or replaced).
-
E.
thirdRedenominationYear
Indicates the calendar year in which the third redenomination event of a currency or financial instrument 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_69a88600b2f88190bc09303e68ab517e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69abb16c09e48190a345c95eab59fd87 |
completed | March 7, 2026, 5:02 a.m. |
| PD | Predicate disambiguation | batch_69abafe02c3c819093a4744b476106ca |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb16a6db48190af04012e8ed2269f |
completed | March 7, 2026, 5:02 a.m. |
Created at: March 4, 2026, 7:34 p.m.