Triple
T1911695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intermediate-Range Nuclear Forces Treaty |
E38123
|
entity |
| Predicate | approximateNumberOfMissilesEliminated |
P33881
|
FINISHED |
| Object | about 2,700 |
—
|
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: about 2,700 | Statement: [Intermediate-Range Nuclear Forces Treaty, approximateNumberOfMissilesEliminated, about 2,700]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfMissilesEliminated Context triple: [Intermediate-Range Nuclear Forces Treaty, approximateNumberOfMissilesEliminated, about 2,700]
-
A.
usesMissileSystem
Indicates that one entity employs or operates a particular missile system as part of its capabilities or actions.
-
B.
numberOfMissions
Indicates the total count of missions associated with a given entity or context.
-
C.
numberOfCityGatesDestroyed
Indicates the quantity of city gates that have been destroyed in a given context or event.
-
D.
numberOfShotsFired
Indicates the total count of shots that were discharged in the described event or action.
-
E.
numberOfExplosions
Indicates the count of distinct explosion events associated with an entity or situation.
- 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_69a8862a26088190aae5243695aeefc0 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb34d94fc8190a5bf1e582c77c725 |
completed | March 7, 2026, 5:10 a.m. |
| PD | Predicate disambiguation | batch_69abafeba3d88190afcce67483d8625b |
completed | March 7, 2026, 4:56 a.m. |
| PDg | Predicate description generation | batch_69abb34c4a64819096e12b152b84c334 |
completed | March 7, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:35 p.m.