Triple
T9387698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S1850M long-range radar |
E225944
|
entity |
| Predicate | trackCapacity |
P88654
|
FINISHED |
| Object | more than 1000 targets |
—
|
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: more than 1000 targets | Statement: [S1850M long-range radar, trackCapacity, more than 1000 targets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: trackCapacity Context triple: [S1850M long-range radar, trackCapacity, more than 1000 targets]
-
A.
transportCapacity
Indicates the maximum quantity of people, goods, or materials that can be transported by an entity or system within a given operation or time frame.
-
B.
capacityRecord
Indicates a recorded measure of how much of a resource, space, or system is available or can be utilized at a given time.
-
C.
ramCapacity
Indicates the amount of system memory (RAM) that an entity possesses or supports.
-
D.
typicalCapacity
Indicates the usual or standard amount, volume, or capability that something is designed or expected to hold, handle, or perform under normal conditions.
-
E.
dataCapacity
Indicates the maximum amount of data that something can store, handle, or transmit.
- 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_69ca842e9dcc8190a264119e683cfe04 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd50d562a48190875d9fe3aae25a2b |
completed | April 1, 2026, 5:07 p.m. |
| PD | Predicate disambiguation | batch_69cca53bd6ec81909bf403ce304e5c08 |
completed | April 1, 2026, 4:55 a.m. |
| PDg | Predicate description generation | batch_69cca89b3368819087a3d69270c1f185 |
completed | April 1, 2026, 5:09 a.m. |
Created at: March 30, 2026, 7:45 p.m.