Triple
T22958445
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vela nuclear test detection satellites |
E570823
|
entity |
| Predicate | numberOfOperationalPairs |
P55010
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Vela nuclear test detection satellites, numberOfOperationalPairs, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfOperationalPairs Context triple: [Vela nuclear test detection satellites, numberOfOperationalPairs, 6]
-
A.
numberOfPairsUsed
chosen
Indicates the quantity of distinct pairs involved or utilized in a given context or operation.
-
B.
numberOperational
Indicates that an entity is currently functioning and available for use in its intended operational capacity.
-
C.
numberOfOperationalCommands
Indicates the total count of operational command units or directives associated with a given entity or context.
-
D.
partnerCount
Indicates the number of partners associated with a given entity in the relationship.
-
E.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
- F. None of above.
Provenance (3 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_69e245b212a88190b5259caf51606084 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f181f2ce9c8190977f146771816341 |
completed | April 29, 2026, 3:58 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:47 p.m.