Triple
T18300747
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MPE (Multi-Agent Particle Environments) |
E438350
|
entity |
| Predicate | typicalNumberOfAgents |
P99351
|
FINISHED |
| Object | multiple agents per environment |
—
|
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: multiple agents per environment | Statement: [MPE (Multi-Agent Particle Environments), typicalNumberOfAgents, multiple agents per environment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfAgents Context triple: [MPE (Multi-Agent Particle Environments), typicalNumberOfAgents, multiple agents per environment]
-
A.
numberOfAgents
Indicates the quantity of agents involved in or associated with a given entity or situation.
-
B.
typicalNumberOfPlayers
chosen
Indicates the usual or standard number of players involved in participating in an activity or game.
-
C.
hasNumberOfTradersApproximate
Indicates an approximate or estimated count of traders associated with an entity.
-
D.
estimatedMemberCount
Indicates the approximate or predicted number of members associated with an entity.
-
E.
slotCountTypical
Indicates the usual or standard number of slots associated with an entity under normal conditions.
- 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_69d8b915e3e881909125d760c15d0c29 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e5017f63dc819083a675d570620f2f |
completed | April 19, 2026, 4:23 p.m. |
| PD | Predicate disambiguation | batch_69e44fdf43d08190bbcfb6b1fe3cc0ee |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:35 a.m.